Tag: machine learning

Posted on by

Collaboration vital for making DEI progress

Thank you for joining!

Access your Pro+ Content below.

February 2025

At the Computer Weekly diversity in tech event, in partnership with Harvey Nash, attendees agreed wholeheartedly that only by working together can we create a truly diverse and inclusive industry. Download the full report here.

Table Of Contents

  • When it comes to increasing the representation of people from all walks of life in the technology sector, complacency is the enemy.
  • It is important to actively create opportunities for underrepresented groups to join the tech sector if we are to make the industry a more diverse place.
  • People working in the IT sector need to be proactive in ensuring the tech workforce reflects tech users.
  • To ensure AI works for us as individuals and as a collective, collaboration is the way forward.
  • There is an imbalance between the number of women using AI and the number of women developing AI, which is contributing towards AI bias and tech that isn’t suitable for all of its users.
  • In some cases, development of AI and machine learning has been biased against women and other underrepresented groups.

Source

Posted on by

DeepSeek-R1: Budgeting challenges for on-premise deployments

Until now, IT leaders have needed to consider the cyber security risks posed by allowing users to access large language models (LLMs) like ChatGPT directly via the cloud. The alternative has been to use open source LLMs that can be hosted on-premise or accessed via a private cloud. 

The artificial intelligence (AI) model needs to run in-memory and, when using graphics processing units (GPUs) for AI acceleration, this means IT leaders need to consider the costs associated with purchasing banks of GPUs to build up enough memory to hold the entire model.

Nvidia’s high-end AI acceleration GPU, the H100, is configured with 80Gbytes of random-access memory (RAM), and its specification shows it’s rated at 350w in terms of energy use.

China’s DeepSeek has been able to demonstrate that its R1 LLM can rival US artificial intelligence without the need to resort to the latest GPU hardware. It does, however, benefit from GPU-based AI acceleration.

Nevertheless, deploying a private version of DeepSeek still requires significant hardware investment. To run the entire DeepSeek-R1 model, which has 671 billion parameters in-memory, requires 768Gbytes of memory. With Nvidia H100 GPUs, which are configured with 80GBytes of video memory card each, 10 would be required to ensure the entire DeepSeek-R1 model can run in-memory. 

IT leaders may well be able to negotiate volume discounts, but the cost of just the AI acceleration hardware to run DeepSeek is around $250,000.

Less powerful GPUs can be used, which may help to reduce this figure. But given current GPU prices, a server capable of running the complete 670 billion-parameter DeepSeek-R1 model in-memory is going to cost over $100,000.

The server could be run on public cloud infrastructure. Azure, for instance, offers access to the Nvidia H100 with 900 GBytes of memory for $27.167 per hour, which, on paper, should easily be able to run the 671 billion-parameter DeepSeek-R1 model entirely in-memory.

If this model is used every working day, and assuming a 35-hour week and four weeks a year of holidays and downtime, the annual Azure bill would be almost $46,000 a year. Again, this figure could be reduced significantly to $16.63 per hour ($23,000) per year if there is a three-year commitment.

Less powerful GPUs will clearly cost less, but it’s the memory costs that make these prohibitive. For instance, looking at current Google Cloud pricing, the Nvidia T4 GPU is priced at $0.35 per GPU per hour, and is available with up to four GPUs, giving a total of 64 Gbytes of memory for $1.40 per hour, and 12 would be needed to fit the DeepSeek-R1 671 billion-parameter model entirely-in memory, which works out at $16.80 per hour. With a three-year commitment, this figure comes down to $7.68, which works out at just under $13,000 per year.

A cheaper approach

IT leaders can reduce costs further by avoiding expensive GPUs altogether and relying entirely on general-purpose central processing units (CPUs). This setup is really only suitable when DeepSeek-R1 is used purely for AI inference.

A recent tweet from Matthew Carrigan, machine learning engineer at Hugging Face, suggests such a system could be built using two AMD Epyc server processors and 768 Gbytes of fast memory. The system he presented in a series of tweets could be put together for about $6,000.

Responding to comments on the setup, Carrigan said he is able to achieve a processing rate of six to eight tokens per second, depending on the specific processor and memory speed that is installed. It also depends on the length of the natural language query, but his tweet includes a video showing near-real-time querying of DeepSeek-R1 on the hardware he built based on the dual AMD Epyc setup and 768Gbytes of memory.

Carrigan acknowledges that GPUs will win on speed, but they are expensive. In his series of tweets, he points out that the amount of memory installed has a direct impact on performance. This is due to the way DeepSeek “remembers” previous queries to get to answers quicker. The technique is called Key-Value (KV) caching.

“In testing with longer contexts, the KV cache is actually bigger than I realised,” he said, and suggested that the hardware configuration would require 1TBytes of memory instead of 76Gbytes, when huge volumes of text or context is pasted into the DeepSeek-R1 query prompt.

Buying a prebuilt Dell, HPE or Lenovo server to do something similar is likely to be considerably more expensive, depending on the processor and memory configurations specified.

A different way to address memory costs

Among the approaches that can be taken to reduce memory costs is using multiple tiers of memory controlled by a custom chip. This is what California startup SambaNova has done using its SN40L Reconfigurable Dataflow Unit (RDU) and a proprietary dataflow architecture for three-tier memory.

“DeepSeek-R1 is one of the most advanced frontier AI models available, but its full potential has been limited by the inefficiency of GPUs,” said Rodrigo Liang, CEO of SambaNova.

The company, which was founded in 2017 by a group of ex-Sun/Oracle engineers and has an ongoing collaboration with Stanford University’s electrical engineering department, claims the RDU chip collapses the hardware requirements to run DeepSeek-R1 efficiently from 40 racks down to one rack configured with 16 RDUs.

Earlier this month at the Leap 2025 conference in Riyadh, SambaNova signed a deal to introduce Saudi Arabia’s first sovereign LLM-as-a-service cloud platform. Saud AlSheraihi, vice-president of digital solutions at Saudi Telecom Company, said: “This collaboration with SambaNova marks a significant milestone in our journey to empower Saudi enterprises with sovereign AI capabilities. By offering a secure and scalable inferencing-as-a-service platform, we are enabling organisations to unlock the full potential of their data while maintaining complete control.”

This deal with the Saudi Arabian telco provider illustrates how governments need to consider all options when building out sovereign AI capacity. DeepSeek demonstrated that there are alternative approaches that can be just as effective as the tried and tested method of deploying immense and costly arrays of GPUs.

And while it does indeed run better, when GPU-accelerated AI hardware is present, what SambaNova is claiming is that there is also an alternative way to achieve the same performance for running models like DeepSeek-R1 on-premise, in-memory, without the costs of having to acquire GPUs fitted with the memory the model needs.

Source

Posted on by

Quantum computing in cyber security: A double-edged sword

Despite investor scepticism, prominent quantum computing stocks have seen a notable rise at the beginning of 2025. Even prominent tech leaders like Jensen Huang and Mark Zuckerberg stating the field won’t be profitable hasn’t stopped investors and the wider public from being excited. 

In cyber security, however, quantum computing offers both unprecedented capabilities and significant threats, making it a double-edged sword that demands careful navigation. Just as white hat hackers can use it to bolster defences, their malicious counterparts might be able to supercharge their efforts, too. 

But how do we grapple with this quantum quandary? That’s exactly what we’ll tackle in this article, as we must collectively ensure they are not blindsided by the risks while leveraging its advantages.

Due to the presence of qubits, quantum systems can perform multiple calculations simultaneously, exponentially increasing computational power for specific tasks. 

For cyber security, we already know this means quantum computers could break widely used encryption methods, particularly those relying on factoring large prime numbers, such as RSA and ECC.

These encryption standards form the backbone of secure online communication, financial transactions, and digital identity verification.

The versatility of quantum computing goes beyond cracking encryption. Its computational power could revolutionise cyber security applications by improving pattern recognition, anomaly detection and optimisation algorithms. Tasks that once took days or months to process could be executed within minutes, drastically reducing response times to potential threats.

Breaking encryption: A looming threat

Classical cryptography, based on mathematical problems too complex for current computers to solve within a practical timeframe, faces obsolescence in the quantum era. Shor’s algorithm, a quantum computing method, can efficiently factorise large integers, undermining RSA encryption’s security. 

Just for comparison, in the context of Shor’s algorithm:

  • A traditional computer might need trillions of years to crack a 2,048-bit RSA key.
  • A quantum computer would need hours, if not days, to perform the same action. 

Similarly, elliptic curve cryptography (ECC), celebrated for its efficiency, is vulnerable to the same algorithm. This vulnerability jeopardises everything from personal data protection to national security. 

Hence, experts fear that hackers equipped with quantum capabilities could decrypt intercepted communications, exposing sensitive corporate or governmental information. And we all know how hard it is for politicians to adapt to modern tech. 

Even data encrypted today could be at risk due to the “harvest now, decrypt later” strategy, where adversaries collect encrypted data now, anticipating quantum decryption in the future. The implications extend to industries like banking, healthcare and energy, where secure communication is paramount.

Strengthening cyber security with quantum technology

It’s not all doom and gloom, as quantum computing offers plenty of tools to counter these threats. Quantum Key Distribution (QKD), for instance, uses quantum mechanics to establish secure communication channels. As a result, any attempt to eavesdrop on quantum-transmitted keys would alter their state, immediately alerting both parties to the intrusion.

In addition to QKD, quantum random number generation (QRNG) is another promising application. Unlike classical methods, which rely on algorithms that could be predicted or replicated, QRNG leverages the inherent unpredictability of quantum processes to create genuinely random sequences. This strengthens cryptographic protocols, making them more resistant to attacks.

Last, but most certainly not least, quantum-enhanced machine learning could also aid in identifying and mitigating cyber threats. If the current applications of ML seem daunting, think of what quantum ML can do by analysing vast datasets more efficiently than classical systems. Quantum algorithms could detect subtle patterns indicative of an attack, enabling earlier intervention.

Post-quantum cryptography: The immediate response

The cyber security industry is not waiting passively for the quantum threat to materialise. Post-quantum cryptography (PQC) aims to develop encryption algorithms resistant to both classical and quantum attacks. 

Standards bodies like the National Institute of Standards and Technology (NIST) are already advancing PQC algorithms, with several candidates already released or in the final stages of evaluation.

Despite the apparent defensive potential, transitioning to PQC involves significant logistical challenges. Organisations must inventory their cryptographic assets, evaluate quantum risks and implement new algorithms across their systems. 

For industries like finance and healthcare, where data sensitivity is paramount, the transition timeline could stretch into years, requiring immediate action to stay ahead of quantum advancements. 

The degree of difficulty gets even higher if legacy systems are being relied upon, as backwards compatibility in a quantum context isn’t something developers of old thought about. 

Likewise, PQC adoption requires extensive testing to ensure compatibility with existing systems and resilience against emerging threats. This, unfortunately, means allocating additional resources to train personnel, upgrade infrastructure and maintain compliance with evolving regulatory requirements.

Mr Hyde: How cyber criminals benefit from quantum computing

We’ve spent a lot of time discussing how quantum computing can aid in defending our data, but white hat hackers and red teams aren’t the only ones interested in these advancements. 

Nation states and cyber crime conglomerates with nine-figure sums to spend will certainly finance the R&D of offensive tools, which can pose problems for everyone from governments to small businesses. 

In particular, sophisticated attacks, such as quantum-enhanced phishing or cracking biometric data, could exploit quantum-powered pattern recognition to unprecedented degrees. These capabilities pose a direct threat to authentication mechanisms, access controls and user trust.

Overnight, staples like QR codes and various forms of MFA will become easily corruptible due to the sheer computing power at the criminals’ disposal. Widely used for payments and authentication, they may require updates or complete overhauls to resist quantum-generated attacks. 

Even the seemingly simple act of scanning a QR code could become a security risk if quantum-powered adversaries exploit flaws in code generation or scanning software.

Regulatory and strategic considerations

Despite claims that quantum computing will become feasible or profitable in several decades, we must still prepare for that inevitable moment. 

Governments and regulatory bodies are beginning to address the quantum challenge. Investments in quantum research and the establishment of frameworks for quantum-safe technologies are gaining momentum. 

For businesses, aligning with these initiatives is critical to ensure compliance and leverage state-of-the-art defences. Will cyber security become more expensive? Inevitably. But at the same time, there will be many more incidents than the 2,200 a day companies experienced in 2024.

Moreover, collaboration between the public and private sectors will play a pivotal role in quantum readiness. Sharing threat intelligence, standardising best practices, and incentivising quantum-safe transitions will strengthen collective security. 

Most importantly, governments must invest in building a robust quantum infrastructure to ensure that technological advantages are not monopolised by adversaries.

But how will we be able to balance between protectionism and benefiting the human race as a whole? We’ll find out sooner or later, that’s for sure.

Preparing for the quantum future

Quantum computing is no longer a distant possibility, but an imminent reality. Organisations of all sizes must adopt a proactive stance, integrating quantum risk assessments into their cyber security strategies. In particular, we must collectively focus on: 

  1. Education and awareness: IT and cyber security teams must receive the right education on quantum concepts and their implications. Building in-house expertise will be critical to navigating the complexities of quantum integration.
  2. Cryptographic inventory: This means mapping current cryptographic use to identify vulnerable assets. It allows organisations to prioritise upgrades where they are most needed.
  3. Adopting PQC: Currently, the best option is to transition to NIST-approved post-quantum algorithms. Early adoption minimises the risk of falling behind competitors or compliance requirements.
  4. Testing quantum services: In addition, it’s up to organisations to pilot technologies like QKD and QRNG to evaluate their practical benefits. Testing in real-world scenarios ensures smooth integration and operational efficiency.

Conclusion

Quantum computing’s dual potential in cyber security – as a tool for both defence and attack – requires a balanced approach. While its threats to traditional encryption are undeniable, its innovations also promise stronger, more resilient defences. 

Organisations that act now to understand and prepare for the quantum era will not only safeguard their assets, but position themselves as leaders in a rapidly evolving technological landscape.

Otherwise, no one’s data will be safe, and we’ll have no way of keeping up with the computing power at the hackers’ disposal.

Source

Posted on by

DeepSeek: Welcome to US artificial intelligence’s Sputnik moment

Following last weekend’s introduction of the latest large language model (LLM) from DeepSeek, ChatGPT’s new artificial intelligence (AI) rival has topped the Apple App Store for iPhone downloads.

The DeepSeek R1 LLM is open source and uses reasoning combined with what the company calls “cold start data”, which means that rather than trawling the internet and social media sites to amass vast quantities of machine learning data, it relies instead on reinforced learning to improve accuracy.

On its GitHub page, the developers of DeepSeek describe R1 as a large-scale reinforcement learning on the base model. “We directly apply reinforcement learning to the base model without relying on supervised fine-tuning as a preliminary step,” it says. “This approach allows the model to explore chain-of-thought for solving complex problems.”

An estimated 2.1 million searches for DeepSeek were recorded over the weekend, with at least 1.6 million of these on Sunday 26 January alone. This is 12.3% of ChatGPT’s 13 million searches in the same timeframe.

Along with taking a different approach to ChatGPT, the interest in DeepSeek is also being driven by competitive pricing and the fact that the code is open source.

While OpenAI, the maker of ChatGPT, charges $2.50 per million input tokens for its GPT-4o model, DeepSeek is priced at $0.14 per million input tokens in situations where the AI engine is able to draw on previously cached information. Non-cached inputs are priced at $0.55 per million tokens.

The extent of interest in the AI from the Chinese firm resulted in turmoil in the valuation of tech stocks in the US. Reuters reported that Nvidia saw its share price drop 17%, which effectively wiped $593bn off its market valuation.

Wake-up call

In a speech on Monday, US president Donald Trump described DeepSeek as a wake-up call for the US tech sector.

Among the numerous subjects Trump spoke about in his speech to Republican party members of Congress were the executive orders revoking the AI regulations introduced under former president Joe Biden. “We don’t want to have any future president ever sabotage our economy with out-of-control regulations,” he said. “Last week I signed an order revoking Joe Biden’s destructive artificial intelligence regulations so that AI companies can once again focus on being the best, not just being the most woke.”

He then referenced DeepSeek as he continued talking about why deregulation is important for AI in the US. “Today and over the last couple of days I’ve been reading about China and [one Chinese company] in particular coming up with a faster method of AI and a much less expensive method. Hopefully the release of DeepSeek AI from a Chinese company should be a wake-up call for our industries that we need to be laser-focused on competing to win.”

DeepSeek’s developers have been able to combine cutting-edge algorithms to slash the energy demands of AI training and deployment. In his speech, Trump described what DeepSeek had achieved as “good”, since companies aiming to develop AI applications that use DeepSeek do not have to spend as much money compared with rival LLMs. “I view that as a positive, as an asset,” he added.
 
Commenting on what the rise of DeepSeek has meant to financial markets, Charu Chanana, chief investment strategist at investment platform Saxo, pointed out that DeepSeek took only two months to develop and less than $6m to build, using reduced-capability chips from Nvidia. This is significant given that the Biden administration banned the export of high-end Nvidia graphics processors (GPUs) to China in 2023.

“US tech companies are trading at premium valuations, with major AI players like Nvidia, Microsoft and Alphabet commanding forward P/E [price to earnings] multiples far above historical averages,” she said. “With these stocks priced for perfection, even minor disruptions, such as DeepSeek proving advanced AI can be built without top-tier chips, could weigh heavily on share prices. For Nvidia, in particular, its role as a key supplier of AI chips makes it vulnerable if demand for its high-end products wanes.”

The idea of lower-cost and more energy-efficient AI coming from DeepSeek appears to have an immediate impact both on the US tech giants and the energy sector, which has been banking on the growth of AI-fuelled power consumption.

“DeepSeek’s breakthrough signals a shift toward efficiency in AI, which will redefine both energy and AI markets,” said Nigel Green, the CEO of global financial advisory giant DeVere Group. “The opportunities for investors willing to act now are enormous.

“This challenges the assumption that AI’s growth is tied to ever-increasing energy consumption. While the market is reacting to short-term uncertainty, efficiency-driven AI models will expand adoption into new markets and industries. This means more widespread use, deeper integration and, ultimately, sustained demand for energy solutions.”

Arguably, it’s the fact that DeepSeek has been able to achieve results using inferior hardware and offer its LLM at a highly competitive price that is set to change every organisation’s approach to AI: it doesn’t necessarily require throwing vast amounts of costly GPUs at the hardware and having to recoup these costs by charging end users a premium.

“By developing cutting-edge generative AI models without relying on the latest, most expensive hardware, DeepSeek has demonstrated that agility and strategy can outpace raw computational power,” said Kjell Carlsson, head of AI strategy at Domino Data Lab. “Their achievements also highlight the vulnerability of incumbents in the generative AI space – proving that open-source innovation continues to be a powerful equaliser, enabling challengers to match and even surpass established players years into the revolution.”

What all this means is that DeepSeek signifies Chinese competition to Silicon Valley’s existing AI models and is a demonstration of how the pace of AI development is pushing boundaries and lowering costs. 

Source

Posted on by

Nato membership boosts Finnish civil and military tech startups

Finland’s fast-expanding defence sector is witnessing a surge in tech startups chasing new business opportunities on the back of the country’s accession to the North Atlantic Treaty Organisation (Nato) in April 2023.  

The so-called Nato dividend is causing the country’s defence sector to experience accelerated growth as more companies capitalise on membership to innovate, grow sales and pursue new avenues of opportunity.  

Buttressed by Nato membership, Finnish tech startups that offer civil and military services are generating comparatively higher growth rates and stronger investor appeal than more traditional defence companies, said Keith Bonnici, investment director at Suomen Teollisuussijoitus (Tesi), a state-owned agency that takes equity-linked financial positions in tech startups and growth companies.  

“The rise in demand for growth capital among startups is tied to the boom in sales in this sector, as well as the sharp increase in export licences,” he said. “As a result, production needs to keep pace with higher demand. Finland remains competitive in the defence industry domain. Our indigenous players have some of the world’s largest defence contractors as customers, as well as Nato members’ defence forces.”  

A Tesi survey released in September 2024 described 144 of the 368 companies currently operating in Finland’s defence sector as “rapidly growing startups and growth companies”.

“We estimate that the annual revenue growth rate of technology companies that offer civilian and military products is as high as 30% to 40%,” said Bonnici. “This clearly exceeds growth rates being achieved by traditional defence companies. The level of growth we are seeing explains why private equity and venture capital investors favour these dual-use companies. Over one-third of the dual-use firms surveyed are owned by private equity and venture capital investors.” 

The Tesi survey found that venture capital financing was the largest individual source of capital investment for companies offering dual-use defence products during the first three quarters of 2024. Moreover, the survey identified the Finnish state as a significant player in the sector, with state-affiliated companies having invested in over 40 defence industry firms since 2014.

Record sales forecast

Buoyed by the “Nato dividend” and bolstered confidence among dual-product tech startups, Finland’s defence sector is on course to deliver a record surge in export sales by 2030, said Bonnici.    

“Finland’s total defence related exports amounted to €2.6b in 2023,” he added. “Based on the latest data and trends, there is every confidence to believe that total annual exports may well reach the €10bn milestone by 2030.”

Helsinki-based Varjo Technologies has expanded development of dual products to reflect a heightened demand for its virtual reality (VR) pilot flight training wares.

Finland’s new status in Nato has substantially improved its ability to achieve stronger international growth, said chief executive Timo Toikkanen. “Nato membership has created new opportunities to grow sales of our VR flight training products,” he said. “It makes it easier to build a presence in the civilian and defence aerospace sectors.”

The Nato factor came into play for Varjo in August 2024, when the US Federal Aviation Administration (FAA) approved the use of its VR headsets to support helicopter pilot training. VR technology is being more broadly tested by Nato-aligned air forces that view it as a cost-efficient option to supplement or replace traditional pilot training in aircraft and large simulator room environments.  

In advance of certification by the FAA, Varjo’s VR-headset hardware had been previously authorised for dual defence and civilian use by the European Aviation Safety Authority, in connection with Swiss group Loft Dynamics’ helicopter pilot flight simulation training device.

Historically, dual-product startups faced serial hurdles trying to generate significant levels of investor interest from defence-shy private equity funds and venture capital firms, said Toikkanen. “Being a dual-product tech company and supplier to the defence industry is nowadays seen not only as acceptable, but even a good thing from the perspective of investors,” he added.

VR investments

Toikkanen attributed the €34m operating loss reported by Varjo in 2023 to the company’s need to make large upfront investments to develop its fourth-generation VR headset. Varjo is hoping to raise next-stage funding of €8m in 2024–2025.   

The dual-product business opportunities flowing from Nato membership are also boosting sales confidence at Saab, the Nordic region’s largest defence technology group. 

Saab reorganised a number of core units under new leadership after Sweden’s membership of Nato was ratified in March 2024. Sweden’s accession to Nato has enhanced the company’s belief in sustainable growth through technology-led projects and capital investments, said Micael Johansson, Saab’s CEO. “We are moving towards establishing a production presence in Ukraine in collaboration with defence and technology companies there. It may be a year or more before this plan takes shape,” he said.  

Saab is hoping to find technology partners in Ukraine to develop and produce a wide range of defence and security wares, including next-generation sensors to leverage Ukraine’s existing drone capabilities. 

Ukraine is exploring the possibility of partnering Saab to produce a range of high-grade military equipment, including Command, Control, Communications, Computers and Intelligence (C4I) and AI/GPS battle management systems in addition to advanced data fusion technologies.

Saab’s new generation of AI and machine learning (ML) product offerings have attracted interest across the Nato member countries. In September last year, it secured a contract to deliver Near Real Time (NRT) AI/ML models to US cyber security and cloud group ECS Federal.

ECS is deploying Saab’s NRT AI/ML technology as part of its input to the US Department of Defense’s (DoD) Maven Program, which is designed to process imagery and full-motion video from drones and automatically detect potential targets.

Joint defence

The growth path to Nato contracts for dual-product firms in Finland and Sweden was greatly enhanced in September 2024, when Nordic governments launched a Regional Joint Defence Concept.  

The agreement, which is managed by the Nordic Defence Cooperation (Nordefco), will synchronise key areas of military cooperation including capacity building, linked military operations, defence technology development and joint products procurement schemes, on a regional level.

Established in 2009, Nordefco serves as a coordinating agency for cross-border defence cooperation between the five Nordic states.

Regionally, the future growth potential of dual-product and defence tech startups across the Nordics is further boosted by Finland and Sweden’s Limited Partner status in the Nato Innovation Fund (NIF). The NIF is financed by 24 of Nato’s 32 member states.  

Capitalised at €1bn, the NIF primarily invests in deep tech defence and security companies across alliance states, while taking a special investment interest in firms developing AI, ML and space technologies.  

“The Nato Innovation Fund is a hugely influential tool to drive technological innovation and development throughout Sweden’s defence and security industries,” said Pål Jonson, Sweden’s defence minister. “For Sweden, it’s an additional benefit of being part of Nato.”

Source

Posted on by

Innovation, insight and influence: the CISO playbook for 2025 and beyond

As 2024 comes to a close and we reach the midpoint of a decade that might generously be described as having so far been ‘turbulent’, I’d like to inject a note of positivity regarding the outlook for the second half of the 2020s. 

Before you dismiss me as naïve or irrationally optimistic, please hear me out. I’m not claiming that the cyber security threats facing CISOs and their teams aren’t extremely problematic. On the contrary, threat actors are adopting AI to mount more complex and sophisticated attacks. This is a trend we can expect to continue in the second half of the 2020s. 

But this is exactly why we cyber security professionals cannot afford to be immobilised by fear, uncertainty and doubt. To borrow a line from the Frank Herbert sci-fi epic Dune, “Fear is the mind killer.” And the broader business community must avoid paralysis too. What’s clear is, the nature of today’s threat landscape demands a united front.

To help allay fear, cyber security professionals can create a robust plan and a playbook of strategies that we can be confident will service us well. With that in mind, I’d like to propose that CISOs and their teams focus on continuing to build three key attributes in 2025 and beyond: innovation, insight and influence. 

Innovation is vital

Innovation is a vital element of the CISO playbook for 2025 and beyond. In the next five years, all analysis points to an escalation of cyber security threats driven by artificial intelligence (AI), and I firmly believe we must fight fire with fire. In other words, just as malicious actors have been quick to master and weaponise AI to conduct their attacks, AI can help cyber security teams build robust defences. 

Cyber criminals are already using AI to automate attacks, to identify vulnerabilities in corporate systems, and to create attacks that are more likely to evade detection. In response, cyber security teams should be using AI to proactively patch any points of weakness, to spot suspicious anomalies in traffic flows and user behaviours, and to stop them in their tracks. AI provides the bridge between security data and actionable knowledge at scale. 

In short, smart cyber security teams will get AI working for them. They will tap into its analytic powers and automation capabilities to craft proactive and adaptive strategies that reduce their reliance on traditional rules-based detection and manual effort.  

Insight matters

Insight matters because we need to recognise and acknowledge that cyber threats are changing. Ransomware, phishing, zero-day exploits haven’t gone away – but increasingly, cyber security teams must also consider their approach to deepfake attacks, based on fraudulent but highly convincing images and multimedia files purporting to relate to real people. 

The use of deepfakes by malicious actors is on the rise. In February 2024, Hong Kong police authorities reported that a finance worker at a multinational firm was tricked into paying out $25m to fraudsters who use deepfake technology to pose as the company’s own chief financial officer in a video conference call. The firm was later revealed to be engineering giant Arup

In May, Mark Read, the CEO of the world’s largest advertising company WPP, became the target of an elaborate deepfake scam, in which fraudsters created a WhatsApp account with a publicly available image of Read and used it to set up a Microsoft Teams meeting that appeared to be with him and another senior WPP executive. In this case, the attempt to solicit money and personal data was unsuccessful. 

Other firms will be targeted, as the underlying technology becomes more accessible and affordable for threat actors. According to IT market analyst company Gartner, by 2026, almost one-third of organisations (30%) will consider their current authentication or digital ID tooling inadequate to fight deepfakes. 

With that in mind, during 2025, IT security teams must step up and play an instrumental role in helping to counter this kind of sophisticated social engineering attack, by educating executives and employees on the risk, training them to spot deepfakes, and putting advanced AI and machine learning capabilities to work on identifying and deterring them. 

Security influencers

Finally, CISOs must continue to engage more broadly with business to understand its priorities. The CISO’s expertise and opinions must directly impact business strategy and they are important interlocutors in boardroom discussions about organisational risk. 

Today’s CISO is more frequently involved in strategic conversations and needs a sound understanding of overall business priorities in order to build programmes that manage risk exposure effectively. In short, the role is expanding significantly as cyber attacks become an ever-more complex and prominent part of the overall enterprise risk picture. 

This trend will see CISOs working more closely than ever with other senior executives, including those involved in overseeing finance, legal, HR and operations, as well as with those at the very top of the corporate hierarchy. A recent survey from Deloitte Global, for example, shows that one in five businesses worldwide now has the CISO report directly to the CEO, rather than the chief information officer.

According to the report’s authors: “Today CISOs are not only protectors against outside threats, but key players helping their organisation find success by integrating cyber considerations in the strategic decision-making process.”

I couldn’t agree more. Innovation, insight and influence are just three elements of my own strategy for 2025 and beyond – others include inclusivity and imagination – but I believe they will go a long way in helping us to face the future with determination and a positive mindset.

Source

Posted on by

Interview: Wendy Redshaw, chief digital information officer, NatWest Retail Bank

Wendy Redshaw, chief digital information officer (CDIO) at NatWest Retail Bank, has had a distinguished career leading technology-led change in some of the world’s biggest financial services organisations. Now, she’s using that experience to drive even more innovation.

After four years as CIO for collaborative technology solutions with Deutsche Bank, Redshaw says she was eager to work for a UK finance house. In late 2018, she found the perfect home at NatWest as head of technology and digital distribution for the personal bank.

“The opportunity was interesting because NatWest was ready for digital transformation but wasn’t naturally sitting in a leadership position at that time,” she says. “The role allowed me to land and think about what to do. I found an organisation that was fundamentally focused on its customers and perhaps had less digital experience in-house.”

After working with her team to deliver technological improvements across the personal bank offline and online, Redshaw moved into the CDIO position in February 2020. “It wasn’t just because I wanted a longer acronym than most technologists,” she jokes.

“We created the role so we could sew together business and technology because, as with many organisations, technology had historically been something that happened over there, and the business did their thing, and then they would give the technologists something to work on. We wanted better integration.”

Embracing digital change

Redshaw says the creation of her CDIO role in 2020 was a public statement that NatWest wanted to create a partnership approach to technology and business: “This is a digital bank in the making, and hopefully, with the results that we’ve seen, we’ve achieved our aims.”

The technological transformation in banking services that Redshaw oversees at NatWest today differs greatly from the finance industry she joined as a software engineer in 1987.

“We didn’t call it digital then,” she says. “I remember the focus was on, ‘How do we use technology to make things quicker, simpler and more secure for our customers?’” She points to work on a security module for the London Stock Exchange and the beginning of the settlement systems CHAPS and Euroclear.

“There was a lot of change where technology was being brought in, but it was more for the underpinning services than for the consumer-facing areas,” she says, before fast-forwarding to the present-day bank. “Over that time, we’ve seen that digital is now in the hands of our retail customers.”

Redshaw says the shift in technological focus also helped prompt her switch to the retail side of banking. After a career driving behind-the-scenes IT changes in major firms, such as Lloyds TSB, Barclays Capital and Royal Bank of Scotland, her current role at NatWest is focused on delivering innovative customer services.

“That’s where the exciting stuff is happening. Yes, of course, we use AI across several areas of the organisation – something like 17% of our models are AI-based now, such as for controlling fraud, financial crime and so on,” she says.

“However, in terms of affecting human beings, digital services are at our customers’ fingertips. If you think about my driver for going into the CDIO role, the customer is where I thought I’d have the most impact.”

Delivering pioneering innovations

As CDIO, Readshaw is directly accountable to the group CIO and retail banking CEO. Responsible for digital operations leadership, she manages 4,500 people across four locations globally and leads the delivery of retail banking technology for Royal Bank of Scotland, NatWest and Ulster Bank North.

Redshaw’s team is digitalising services to make life easier for the group’s customers. Their work is supported by a planned investment of £3.5bn from 2023 to 2025, with more than 70% of spending targeted at data and technology.

NatWest has 10.9 million digitally active retail and business banking customers and 3.5 million use online banking platforms. The hard work continues apace. In 2024, Redshaw led the launch of a retail banking app on Apple’s Vision Pro virtual reality headset.

One of her proudest achievements is the introduction of generative AI (GenAI) into the bank’s conversational assistant, Cora. She says the bank made an early move into chatbots. Cora was introduced in 2017. The technology could answer basic questions, but Redshaw wanted it to do more.

“When I joined in 2018, I realised it was quite a good channel to do something with,” she says. “I had some grand ambitions for her – things like digital avatars having a voice, and all these engaging ways of doing things. I said, ‘Look, I see this particular technology being something we could get moving on’.”

Redshaw saw that, while machine learning technology was progressing at pace, it wasn’t quite ready for the giant leap in digital experiences she envisioned. However, the public release of generative AI models in late 2022 helped turn theory into a practical reality. Working with experts from IBM’s client engineering team to develop the initial proof of concept, NatWest launched its next-generation assistant, Cora+, in June 2024.

Cora+ is a multichannel platform that securely accesses data from multiple sources, including products, services and banking information. The virtual assistant technology is powered by IBM’s Watsonx Assistantand built on IBM Cloud. Estimates suggest the technology is creating a 150% improvement in satisfaction for some customer queries.

“It was the perfect example of an interest in technology, an interest in people, and an interest in delivering business value,” she says. “I feel very excited about how we’ve taken something that just answered questions and moved into generative AI at scale for millions of customers. And it’s only the first step. I’ve got big ambitions for what I want to do with that technology.”

Building strong partnerships

Cora+ uses ChatGPT 3.5 alongside an unnamed GPT large language model (LLM). The second model is trained to judge the output of the first model. While the GPT models play an important role in NatWest’s digital strategy, the organisation is eager to keep an open approach to AI and innovation.

Redshaw says the group wants to avoid being locked into a specific LLM. She wants the capability to swap from large to small language models (SLMs). Organisations can use SLMs to derive outputs from constrained amounts of data that require less computing power, which is important for a big business like NatWest that wants to meet sustainability targets.

“As a result, it was a case of, ‘OK IBM, we like working with you, but we want to be able to switch the language models in and out depending on the business requirement’,” she says. “And they were like, ‘Absolutely’. So, that’s great. We have the same mindset around using the best of everything to get value for our customers safely.”

Wendy Redshaw, Natwest

“This is a digital bank in the making, and hopefully, with the results that we’ve seen, we’ve achieved our aims”

Wendy Redshaw, NatWest Retail Bank

In addition to the work on Cora+, Redshaw and her colleagues are analysing how AI can boost customer experiences in other areas. NatWest has worked with IBM to develop a digital legal assistant powered by GenAI. This tool streamlines contract management and enhances accessibility, especially for neurodivergent users. The tool supports colleagues with compliance checks, producing 20% efficiency gains.

More generally, Redshaw is proud her team completes thousands of releases annually. The department’s focus on micro-projects is as important as delivering large-scale initiatives and helps NatWest hit tight transformation deadlines. Across all projects, IBM acts as a key technology partner, with Redshaw suggesting the nature of the long-term working relationship with the tech giant is like interacting with people on the internal team.

John Duigenan, distinguished engineer and general manager of the global financial services industry at IBM, says shifting to constant innovation, experimentation, and learning is typical of the work his company sees in its most pioneering clients. “We got to work with a trusted partner, and we got to learn together,” he said, referring to IBM’s relationship with NatWest.

“It’s great we co-create approaches to using technology and collaborate on innovation. Our teams blend incredibly well, and we deliver together in new ways. We have an approach that says, ‘We know why this work will matter for all of us because we can measure the impact’.”

Providing new experiences

Redshaw reflects on achievements during the past few years. While the benefits of the digital transformation she’s enacted at NatWest are clear, there’s always an opportunity to do more.

She says the rapid pace of transformation makes it difficult to predict with any degree of certainty what will happen next: “What will the success metrics be in three years? We won’t be judged on the same metrics because digital banking is changing quickly.”

However, she expects to see developments in some key areas. “In the AI space, I expect to see more voice,” she says. “At the moment, Cora listens to our telephony and sends a text, a deep link, or something else that’s required. In the future, I think it’ll probably answer the phone and deal with questions.”

Redshaw also expects progress in text-based answering. Her bank’s research suggests people in financial difficulties often prefer having a guilt-free conversation with a bot rather than a human. “I would expect something in that financial health and support space that uses natural language,” she says.

There’s even the potential for advances in unexpected areas. Redshaw says she’s keen to add Cora to ATMs, something that she was previously told was impossible.

“I’ve now spoken to some innovation engineers, and they’ve said they think it might be possible,” she says. “So, I suspect we will see something like a digital point of presence.”

Finally, Redshaw expects the bank to continue honing its approach to mobile. “People now have their bank in their pocket,” she says. “I imagine we will give more richness and engagement through these devices. Even though our mobile strategy is great, I think it will lean towards more engagement and personalisation during the next 24 months.”

Source

Posted on by

The most pressing challenges for CISOs and cyber security teams

The UK Ministry of Defence recently published its Global Strategic Trends report which sets out the developments that will shape the world over the next five years. These provide an insight into some of the challenges that CISOs and cyber security teams will face.

The first threat is that of global and regional political instability. As regional and global power competition intensifies, we may see growing authoritarianism and a decline in democracy. The capabilities of violent extremist organisations and organised crime groups to cause harm will increase. Access to data will become a key component of global power for both state and non-state actors, all of which will require greater vigilance from cyber teams.

The second area of concern comes from the expanding attack surface, The exponential reliance on data and connectivity across states, organisations, and individuals in an increasingly connected world will significantly expand the attack surface. With stretched resources from dealing with an ageing population and climate change, nation states may not be able to provide the increasing level of direct support needed for cyber defence operations.

A further trend driving cyber threats is the technological arms race. The increased reliance on data and connectivity, coupled with advances in Quantum and AI, will escalate the arms race between cyber exploiters and victims. This shift is already being seen in the rise of zero-day attacks. The National Cyber Security Centre (NCSC), in collaboration with cyber security agencies from the US, Australia, Canada, New Zealand, and others, identified that most of the top 15 vulnerabilities exploited in 2023 were initially targeted as zero-day attacks. This trend has continued into 2024, highlighting the evolving tactics of cyber adversaries and the increasing availability of advanced exploitation tools.

Pressing challenges for CISOs and security teams

Given these trends, the most pressing challenges for CISOs in the next five years will be related to the rise of AI, building a culture that fosters secure behaviours, the threats from insiders, data management and patching and monitoring, as well as the ongoing need for operational resilience.

The rise and risk of AI is increasing as adversaries weaponise AI for malicious purposes, using it to create undetectable malware, automate reconnaissance, and execute deepfake-based scams. Organisations are rapidly chasing the ‘AI dream’, looking at ways in which it can deliver significant business benefits and CISOs will need to make their voice heard at the planning stage to avoid security being seen as a secondary consideration.

Organisations invest heavily in protecting their digital systems, physical assets, and people from adversaries with software solutions to detect cyber threats, restrict access to buildings and safeguard sensitive employee information. However, up to 95% of security incidents typically result from human actions, whether through unintentional errors or intentional breaches. A technical solution alone is not going to keep the future organisation safe. To protect what matters most CISOs should look to leverage the power of their people by embedding the right security behaviours into organisational culture to create an effective first line of defence. A robust security culture ensures every individual within the organisation understands their role in maintaining security and takes proactive steps each day to enhance it. 

Insider threats, whether stemming from intentional actions by malicious employees and contractors or unintentional mistakes by negligent staff, remain a significant source of security breaches. These risks are further amplified by the rise of hybrid work models, which reduce organisational control over devices and network environments. These create additional vulnerabilities that security teams must address through more joined up approaches to physical and cyber security.

Data management and protection is ever more critical as there is more data and greater connectivity to manage. CISOs need to know what their critical data is, where it is located, who has access to it, how it flows, how it is protected, and where it is vulnerable. Understanding their own systems and their residual risks, as well as the risks to their data when it is in the hands of others, is crucial. CISOs also must have confidence in their supply chain and its ability to protect assets properly. Networks and data sources must be appropriately protected both in transit and at rest. Ransomware and phishing remain a persistent and evolving danger, with attacks becoming more targeted and destructive. Meanwhile, the advent of quantum computing poses a looming threat to traditional encryption methods, compelling organisations to prepare for a transition to post-quantum cryptographic standards.

The increasing use of effective zero-day exploits means that we need to stay on top of patching and monitoring, which itself will occur at a faster pace. CISOs must get smarter with protective monitoring so that they can identity suspicious system behaviour as early as possible. They should also make better use of AI and machine learning tools as they develop.

As all these threats increase, security teams will have to prioritise operational resilience so they can respond to natural disasters, geopolitical instability, and supply chain disruptions that can compromise infrastructure and data availability. The growing reliance on third-party vendors and services heightens the risk of supply chain attacks, exposing organisations to vulnerabilities that lie beyond their direct control. Ensuring rapid recovery and effective business continuity will increasingly become central to security strategies.

Many of these threats are not new but their number and impact is growing and it is clear that the task of the CIO is only going get harder in the next five years.

Source

Posted on by

AMD pushes GPU advantage with HPC top spot

The AMD-powered El Capitan supercomputer, housed at the Lawrence Livermore National Laboratory (LLNL), is now ranked as the world’s fastest supercomputer.

Built by HPE, the supercomputer uses AMD Instinct MI300A accelerated processing units (APUs). It achieved a High-Performance Linpack (HPL) score of 1.742 exaflops based on the latest Top500 list. 

The LLNL is using the supercomputer for nuclear security. El Capitan is the first exascale-class machine for the National Nuclear Security Administration (NNSA) and will be used to advance scientific discovery and national security, providing what AMD says is “the computational power necessary to ensure the safety, security and reliability of the nation’s nuclear deterrent without testing”.

It is being used for modelling and simulation capabilities to support NNSA’s Stockpile Stewardship Programme, which certifies the ageing nuclear stockpile and other critical nuclear security missions, such as non-proliferation and counter terrorism. 

“El Capitan is crucial to the National Nuclear Security Administration’s core mission and significantly bolsters our ability to perform large ensembles of high-fidelity 3D simulations that address the intricate scientific challenges facing the mission,” said Rob Neely, director of LLNL’s advanced simulation and computing programme.  

LLNL and the other NNSA at Los Alamos and Sandia National Laboratories are also using El Capitan and its companion system, Tuolumne, to drive artificial intelligence (AI) and machine learning-assisted data analysis. El Capitan will apply AI to high energy density problems such as inertial confinement fusion research, while Tuolumne will be used for unclassified open science applications including climate modelling, biosecurity/drug discovery and earthquake modelling.

Bronis R de Supinski, LLNL’s chief technology officer for Livermore Computing, said: “With AI becoming increasingly prevalent in our field, El Capitan allows us to integrate AI with our traditional simulation and modelling workloads, opening new avenues for discovery across various scientific disciplines.”

AMD said its Instinct MI300X and MI325X accelerators provide AI performance and memory capabilities, while the AMD Instinct MI300A APU puts central processing unit (CPU) and graphics processing unit (GPU) cores and stacked memory together into a single package, enabling “new levels of efficiency and performance” for high-performance computing (HPC) and AI workloads.  

Its EPYC processors and Instinct accelerators are also being used to power many new supercomputing and AI projects and deployments, including Italian energy company Eni, whose HPC 6 supercomputer is powered by AMD EPYC processors and AMD Instinct GPUs. The University of Paderborn is also set to take delivery of a new supercomputer powered by the latest fifth-generation AMD Epyc technology.
   
Separately, IBM and AMD have announced a collaboration to deploy AMD Instinct MI300X accelerators as a service on IBM Cloud. The new service, available in the first half of 2025, will target performance and power efficiency for generative AI models. Through the collaboration, support for AMD Instinct MI300X accelerators is being made available within IBM’s Watsonx AI and data platform, as well as through the Red Hat Enterprise Linux AI inferencing platform. 

Source

Posted on by

Interview: Raymond Boyle, vice-president of data and analytics, Hyatt Hotels

Raymond Boyle, vice-president of data and analytics at Hyatt Hotels, is an experienced executive who helps his business make the most of its information. He is responsible for Hyatt’s data strategy, governance, engineering, science and analytics capabilities. His team’s data-led insights boost customer and colleague experiences.

“I took the opportunity because I love the role,” says Boyle, who joined Hyatt at the start of 2020, having previously been vice-president for data and analytics at Walmart Labs.

“I was very excited about Hyatt as a company and its culture. It gives me everything I enjoyed doing within the data role, including leading the strategic insights and the governance areas.”

At Hyatt, Boyle reports to Amy Weinberg, senior vice-president for loyalty, brand marketing and consumer insights. He has spent his five years at the firm laying the foundations for a business strategy that puts data at the heart of organisational and operational processes.

“I love working in the travel industry,” he says. “It’s a complex business. As a data leader, you get all the stuff you would ever want in terms of delivering a customer and colleague experience and creating effective digital engagement.”

Boyle’s current role is the latest stop on a 30-year professional journey during which he has used data and analytics to fuel innovation and growth. He recognises the role of data chief has changed significantly during his time in the profession. The impact of emerging technologies, such as artificial intelligence (AI), brings even greater challenges.

“It has been a fascinating area for many years,” he says. “The field of data and AI is changing extremely quickly, including the types of things that we take on, the way technology is implemented, the way people engage with it and the cultures we build around it.”

Building data products

Boyle says much of his day-to-day leadership role at Hyatt involves ensuring people around the business are fluent in data and can engage with information assets. He says the work revolves around “the productisation of data” and developing self-service environments that make things easier for employees and customers.

“We think of data as a product, including all aspects around managing information, designing strategies and creating solutions,” he says. “That work covers the data engineering worlds that care for different parts of the business, the platform organisations that manage our foundations, and the data science and machine learning functions.”

Boyle says Hyatt’s data strategy centres on advancing care through insight-driven decisions and automation. The focal point of this strategy is cultivating the best people and evolving the organisation’s data culture.

“We’re working through how people lead in the organisation and thinking about data fluency and the stewardship of information within the business,” he says. “We focus a lot on customer personalisation and trust. We want to build the ability for the organisation to be perfect with every guest during every step of their journey and continue to personalise how we engage with our customers in a high-security, high-trust framework.”

Boyle is excited about some of the achievements so far. His team ensures the business has the right data capabilities and performance indicators. At the same time, they make sure people across Hyatt have a common understanding of data-led performance.

“That’s taken a lot of great work to automate and simplify the business from an operational perspective, and then a lot more work to ensure we’re growing with intent – that as we do new mergers and acquisitions as an enterprise, that we can connect data and the products into that system smoothly,” he says.

Innovating at pace

A key underlying technology for this approach is the Snowflake AI Data Cloud for Travel and Hospitality, a unified data platform that helps companies exploit their information. Boyle says Hyatt uses Snowflake technology to consolidate enterprise data into a single location.

The switch to Snowflake took two years to complete and was finished by the second quarter of 2024. Boyle says the move to the AI Data Cloud was an important transition. An ever-increasing number of people at Hyatt wanted to use information. However, the company’s legacy environment had capacity constraints.

“We needed to add a ton of compute to the system, and we had some hard decisions to make as we went through that work,” he says. “We had a massive growth in the amount of data people wanted to consume within the business.”

Raymond Boyle headshot

“We think of data as a product, including all aspects around managing information, designing strategies and creating solutions”

Raymond Boyle, Hyatt Hotels

Boyle’s data team approached the Snowflake implementation carefully and pushed components live incrementally. The switch to Snowflake involved some hard graft. Pipelines were refactored, and the security infrastructure was redesigned. He recognises the migration process was a significant technological and cultural challenge.

“You can’t stop running the business while you execute the migration,” he says. “We had to manage the delivery of many new products and capabilities during the migration. There were times when we had to manage duplicate pipelines. A lot of folks had to be engaged in the migration process.”

The data team decommissioned Hyatt’s legacy environments in August. Snowflake is now the company’s scalable data platform. He says the technology allows people across the business to access data for their projects. The AI Data Cloud also cuts the time his team spends on information management.

“Snowflake allows us to innovate faster and drive those outcomes cleanly over time,” he says. “We’re launching more services, so we have more data applications coming into the system fairly quickly, and we’re also benefiting from Snowflake’s work to ensure that other software organisations are building natively on the platform.”

Supporting business growth

Boyle leads a 100-strong data team at Hyatt, including full-time staff and contractors. He says insight and analytics are at the core of the company’s decision-making processes.

“Data is at the heart of how the company functions,” he says. “Our CEO is engaged in data and has led the strategic work around how we think about AI. Data is now a big part of every domain and a core element of how people plan, build and execute.”

Boyle says one of the company’s data priorities right now is personalisation. “We’re focused on following the customer journey and making sure that AI and data drive the properties that we recommend and the search experience and the content people see,” he says. “We want to ensure our customers have a deeper relationship with Hyatt.”

In addition to its work on personalisation, Boyle says the company is rolling out modern pricing-optimisation capabilities globally. His team is also exploring the potential for generative AI capabilities within analytics. He says there’s no straightforward answer as to whether it’s better to build or buy AI technologies and models.

“It’s likely to be a mix, and the result will depend on what we’re trying to achieve at any given time,” he says. “We’ll look at the outcomes, the initiatives, the strategic investments that the company wants to make, and we’ll make decisions based on the speed and the impact that we want to have, and the architectural standards that we want to see within the organisation.”

Boyle says the data organisation he’d like to lead two years from now will use digital innovation to boost customer experiences and business operations. From self-service behind the scenes to fresh services at the front end, he wants Hyatt to continue transforming with data.

“I want our guests to experience Hyatt in a personalised manner and for us to take full advantage of the relationship we have with our customers. I want to push innovations that ensure our relationship with guests is deeper, more meaningful and more trusted across all the different interaction points we have with them,” he says.

“I’d also want our operations to be more efficient and automated. I want to help our organisation grow with intent. I want to ensure that the types of development we want to do as a business, and the growth the organisation wants to see globally, are better, faster and more efficient due to the data we provide.”

Defining the data chief’s role

Boyle has built his career leading data initiatives at major organisations. He understands successful data chiefs will play a key role in helping businesses to thrive in the digital age. However, they shouldn’t fulfil this role in isolation. Boyle says successful data stewardship is a team game that starts at the top of the enterprise.

“The CEO or the executive team should dictate the direction of travel for AI within the organisation,” he says. “When I think about the operating model, it’s about making sure we have clarity around our purpose and the areas the executives believe are the most important things to invest in. The business leaders for the domains must be aligned to that strategy and work to drive value creation in their functions.”

Boyle says the role of digital leaders, whether CDOs, CTOs or CIOs, is to ensure the hardware and software stack helps business leaders achieve their transformational objectives. Internal and external partners must ensure data is published and consumed effectively and safely.

“The tech stack is critical to your success,” he says. “Enterprise architecture plays a huge role, as does cyber security and the privacy and data governance specialists. If you get those things right, you’ll build out your AI services and the back-end data infrastructure to drive your business outcomes. You’ll be able to scale your initiatives at a faster pace.”

Boyle’s best-practice advice for other data leaders is to think of digital change as a team game. “You need to have fluent, transformational thinkers at all levels. You must have technology partners who are a big part of what you’re trying to do and creating high-quality data tooling,” he says.

“You need to get your product management, engineering, architecture, machine learning and science community functioning together, knowing their roles and delivering joined-up processes quickly and cleanly.”

Source