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8 iOS 18 features that Apple has delayed to 2025

With the launch of iOS 18.2 just around the corner, Apple has a few more iOS 18 features that have now been delayed until 2025.

As excited as we are about all of the new features Apple is bringing to iOS 18, the wait for many of them has been longer than we expected. With that in mind, here are all the features iPhone owners are going to receive sometime next year:

  • Personal context understanding: With Apple Intelligence’s on-device semantic index, Siri can understand emails, messages, photos, calendar events, files, and more and can provide answers to personal questions.
  • In-app actions: Siri can take hundreds of new actions on your behalf in both first- and third-party apps, such as editing a photo, adding a note, and more.
  • Onscreen awareness: Siri will be able to understand and take action with things on your screen, so when a friend texts you recommending a new coffee shop in the neighborhood, you can ask Siri how long it will take to get there.
  • Apple Intelligence expansion: Apple promises Apple Intelligence support will expand to new countries and languages in 2025, most likely around iOS 18.4.
  • Sketch style: With Image Playground, Apple offers animation and illustration styles. However, the Sketch style will likely be delayed. It’s currently available as an option in Image Wand but not for the Image Playground app.
  • Integration with other LLMs: Currently, Apple only offers support for ChatGPT integration with Writing Tools. In the future, the mobile platform is expected to work with other LLMs, such as Google’s Gemini and more.
  • New emoji: Apple usually releases new emojis a few months after its main iOS release. If the company follows the trend, iOS 18.4 could bring new emojis. These are the possible new additions.
  • Robot vacuum cleaners will be compatible with the Home app, so they can participate in automation and scenes and can be activated by a user’s voice using Siri.

iOS 18.1 Apple Intelligence on iPhone 15 Pro all-new Siri designiOS 18.1 Apple Intelligence on iPhone 15 Pro: The all-new Siri design Image source: José Adorno for BGR

While the robot vacuum cleaners feature will likely be released early in 2025 with iOS 18.3, all of these new features will likely be part of iOS 18.4 in the spring.

That being said, it’s possible that most of the Apple Intelligence features related to Siri could be delayed to iOS 19 and beyond. In a previous newsletter, Bloomberg‘s Mark Gurman wrote:

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These upcoming upgrades will make Siri easier to use on a day-to-day basis, but it’s not the brain transplant that the service really needs. Siri is still based on an outdated infrastructure — AI models that have been overtaken by the technology used by ChatGPT and Google’s Gemini. Siri hasn’t yet been rebuilt for the generative AI age, even if Apple is trying to create the impression that it has.

Wrap up

iOS 18 still has several delayed features that might take a long time to become available. Below, you can learn more about what features iOS 18.2 will bring.

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Are you on the naughty or nice list for responsible AI adoption?

Over the past year, artificial intelligence (AI) has proved its worth as a long-term investment for businesses. It brings a range of perfectly wrapped presents to the table, making a significant impact on productivity, efficiency, and automation across business functions. With almost 40% of companies worldwide already using AI in some form, it’s undeniable that it has the capability to revolutionise business operations.

For example, Santa’s workshop would benefit from AI adoption in automation of its supply chain orders, faster and more accurate analysis of wish list data, and tracking of items that have made it into his sleigh.

To ensure he makes the most of AI’s benefits, Santa will have brought it on board with ethical guidelines and responsible practices in mind. But have you? Whether you’ve already adopted and want to make sure you’re using AI responsibly, or you’re yet to adopt and are looking to integrate ethical standards into your plan – time’s running out to get onto Santa’s nice list before Christmas.

Getting into the good books with responsible adoption

Adopting AI responsibly isn’t just about avoiding risks, it’s also a way of setting the stage for sustainable growth, efficiency, and innovation. If you jump on the AI bandwagon without building a solid foundation and outlining a clear strategy, a myriad of risks can await your business. Data breaches, ethical challenges, and financial losses are all risks businesses face if they ignore the importance of responsible adoption.

The most effective way of adopting AI to mitigate these risks is a responsible one, and it’s not as easy as plugging in your Christmas lights. Smart and strategic choices are the key to protecting business data and aligning AI initiatives with business goals.

Santa’s top tips for adopting responsibly

Like writing a Christmas shopping list, AI adoption can be too daunting to start for lots of businesses. With so much information out there, where are you meant to start?

The key is pushing fear to the side and making any type of start, even if it’s small. Those who start now and invest in AI will stay ahead of the curve. But like Rudolph and his crew, the AI gap is real, and businesses who don’t get on board now will be left behind. So, what do you need to consider to adopt AI responsibly?

  • Make sure your data shines like a bauble

Squeaky clean data is crucial to getting reliable insights from AI. Getting AI ready means prepping business operations for AI systems to easily slot in, so business data needs to be accurate, void of bias, and ready for action.

The same way you wouldn’t send Santa a disorganised wish list, you wouldn’t give AI messy data. Making sure data is up to date, without errors or duplicates, is critical to ensuring your AI delivers real value. This comes hand-in-hand with assessing your internal resources, and making sure your infrastructure can handle the scale and power of AI demands. More flexible Cloud platforms like AWS, Google Cloud, and Azure can help business scale AI cost-effectively.

  • Embrace elf-level organisation

Training is a key part of onboarding AI. Do you think Santa’s elves are expected to wrap presents without being trained first? Preparation for AI use is essential to allowing your employees to understand its benefits and using it effectively.

As it affects every team in the business, not just the IT department, the entire workforce needs to be prepped for AI adoption. Whilst this can seem like a costly task, investing in your people is how AI will create valuable results. Change management is a key component to preparing workforces for the changes you need to adopt AI. Fostering a culture of readiness and continuous compliance is key to ensuring it becomes an asset.

Knowing your business objectives and making sure your AI strategy aligns with and contributes to them is key to maximising its capabilities. Whether improving customer experiences, automating repetitive tasks, or personalising services is your business goal, use AI to drive that strategy.

Prioritising AI applications that solve real problems as well as boosting productivity is key to boosting business growth. Do you need help with recommending products to your customers to increase sales? This is a tangible problem AI can solve for you. Like following a gingerbread recipe, baking a strategic AI plan will produce the best goods.

Santa’s secret weapon – Responsible AI

Long-term success is the outcome of adopting AI through responsible practices and with ethical guidelines in mind. High-quality data aligned business goals, and a prepped workforce are the key to thriving rather than falling behind.

If Santa’s already on board, why aren’t you? After all, it’s how he gets his presents from the North Pole to under your tree.

Get onto the nice list this Christmas – start small, think big, and stay responsible.

Kyle Hill is chief technology officer at ANS, a digital transformation provider and Microsoft’s UK Services Partner of the Year 2024. Headquartered in Manchester, it offers public and private cloud, security, business applications, low code, and data services to thousands of customers, from enterprise to SMB and public sector organisations.

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How AI can help you attract, engage and retain the best talent in 2025

As we move into 2025, the landscape of human resources (HR) is heading for a significant transformation. Artificial intelligence (AI) is set to revolutionise workforce collaboration, efficiency, and talent management.

For HR leaders, harnessing the power of AI will be essential to attract, engage, and retain top talent in an increasingly competitive market.

Enhancing HR performance

AI is reshaping and revamping HR by automating routine and mundane tasks such as interview scheduling, data entry, and CV screenings. This automation allows HR teams to focus on strategic initiatives that add real value to employees, such as developing diverse cultures, offering tailored development programmes, and increasing engagement.

AI-powered analytics can identify workforce trends, predict employee turnover, and suggest to retain top talent. These insights enable HR leaders to make data-driven decisions to support a high-performance culture, ultimately improving employee engagement and organisational performance.

Just look at Unilever, which uses AI to streamline its recruitment process. By using AI-driven assessments and video interview analytics, Unilever has significantly reduced time-to-hire while enhancing the candidate experience. Additionally, AI can streamline performance management by providing continuous feedback and personalised development plans. This shift towards real-time performance management fosters a culture of continuous improvement, where the team receives timely feedback and support to achieve their goals, leading to higher engagement levels and better retention rates.

Talent attraction and retention

As the demand on sourcing talent with scarce skills continues in 2025, attracting top talent needs innovative strategies. AI can play a pivotal role in enhancing the candidate experience. Imagine AI-driven chatbots engaging with candidates in real-time, answering their questions and providing personalised information about the company and the role. This immediate engagement can significantly improve the candidate experience, making the organisation more attractive.

AI can also help create a more inclusive hiring processes by eliminating unconscious biases from recruitment. AI algorithms can analyse job descriptions to ensure they are free from biased language and assess candidates based on objective criteria. This is an incredibly important step to support organisations in attracting and growing a more diverse and inclusive workforce, which is crucial for driving innovation and business success.

Retaining your team is equally important as attracting it. AI can help HR leaders identify early signs of people’s disengagement or dissatisfaction. For instance, AI-powered sentiment analysis can monitor employee communications and flag any negative sentiments, allowing HR and managers to intervene proactively. By addressing issues before they escalate, organisations can improve the satisfaction, happiness and ultimately retention of the team.  

AI can also facilitate personalised employee development. By analysing skills, performance data, and career aspirations, AI can recommend tailored development programmes and career paths for each individual. This personalised approach to development can help people feel valued and supported.

Upskilling your team in the New Year

24% of all workers are worried that AI will soon make their job obsolete. HR leaders have a crucial role in addressing these concerns and ensuring their teams are ready for AI integration. Providing training and the right tools to integrate AI smoothly is essential. By fostering a culture of continuous improvement and responsible AI use, HR can drive greater efficiency and empower the entire workforce.

AI is more likely to enhance roles rather than replace them, and HR leaders should embrace AI ethically and transparently. This involves being clear about how AI is used, ensuring data privacy, and maintaining a human touch in all interactions. By doing so, HR can build trust and create a positive environment where AI is seen as a tool for empowerment rather than a threat.

2025 – the future of AI in HR

As we approach 2025 and beyond, the integration of AI in HR will continue to evolve. Future trends may include more sophisticated AI-driven talent management systems, enhanced predictive analytics for workforce planning, and even more personalised employee experiences powered by AI. HR leaders who stay ahead of these trends and continually innovate will be well-positioned to lead their organisations into the future.

Looking to the New Year, AI will play a pivotal role in enhancing HR functions, making them more efficient, strategic, and employee centric. By leveraging AI to attract, engage, and retain top talent, organisations can stay competitive in a rapidly evolving job market. HR leaders who embrace AI responsibly and proactively will be well-positioned to drive their organisations forward, creating workplaces that are both productive and fulfilling for their team.

Toria Walters is chief people officer at ANS, a digital transformation provider and Microsoft’s UK Services Partner of the Year 2024. Headquartered in Manchester, it offers public and private cloud, security, business applications, low code, and data services to thousands of customers, from enterprise to SMB and public sector organisations.

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Six trends that will define cyber through to 2030

Guessing the future is always a difficult task. Six trends for the next five years seem more apparent than others, and it will be interesting to re-read this article in 2029 to assess its accuracy. In the meantime, the six trends standing out as top priorities, in no particular order, are:

Preparing the post-quantum cryptographic migration, including raising top management awareness to provide sufficient resources.

There will be a need to identify where cryptography is used in the organisation, which can be found in several places, including libraries, the Internet of Things (IoT), communication protocols, storage systems, and databases. Prioritizing systems for the transition will be paramount, taking care to clearly identify your critical systems.

Choosing how to manage the transition will also be essential since it may hinder the organisation. More precisely, hybrid protocols, mixing classical and post-quantum cryptography, could be an interesting option to consider, since it allows your clients to migrate at their own pace.

Also, testing will be mandatory, while deploying a realistic test environment might be complex. Finally, the right migration time will be hard to establish, even if governments provide guidelines.

Finalising operational technologies (OT) oversight, improving their cyber resilience, and integrating them into existing cyber security operations.

This convergence started more than 10 years ago and is still ongoing. OT cyber security must include addressing human safety concerns and intensive collaboration with engineering.

The monitoring approach should rely on artificial intelligence (AI) to identify abnormal behaviour, from weak signals, to support advanced persistent threat hunting. Since some systems are legacy, they may lack the necessary features to directly collect the information needed. Encapsulating with an intermediate security system could be a viable solution.

A layered defence strategy and a movement toward a zero-trust architecture might help minimise the attack surface.

Improving cyber security fundamentals, including identity management and network micro-segmentation, and supporting zero-trust architecture while enabling automated threat response.

This leads to implementing robust identity and access management that enforces least-privilege principles and multi-factor authentication.

By integrating policy-based automation, access management becomes more dynamic, transparent and enforceable. Continuous monitoring and real-time analytics should be used to detect anomalies and unauthorised activities, including user behaviour, device posture and geolocation.

Learning how to conduct cyber security for artificial intelligence pipelines (AIOps) while constructing a business case for artificial intelligence-based cyber security, like zero-day attack detection.

This dual focus addresses the sharply increasing complexity of cyber threats and the pervasiveness of AI. As AI continues to revolutionise the landscape, international and domestic regulations are being defined and will become vital to ensure its compliance, resilience and trustworthiness.

Addressing increasing regulations to maintain global compliance, notably for privacy, critical infrastructure, and business continuity.

As stricter rules are adopted, like European Union’s (EU’s) General Data Protection Regulation (GDPR) and AI Act, California’s Consumer Privacy Act (CCPA) for privacy, as well as European Network and Information Systems Directive 2 (NIS2) and CISA guidelines in the United States for critical industries, and more specific requirements from the EU’s Digital Operational Resilience Act (DORA) for the financial industry, organisations need to contextualize these requirements and integrate them into their security posture.

Collaborating closely with third parties, including identifying their Software Bill of Materials (SBOM), and communicating any vulnerability along the supply chain. This will remain an important priority for security leaders as the global enterprise landscape becomes increasingly interconnected.

This should ensure a better understanding of the dependencies toward the third parties, and when an organisation becomes more mature, the broader interdependencies of their ecosystem.

In conclusion, while predicting the near future remains a challenging task, these six top priorities will play a pivotal role in organisational resilience.

As we look ahead, there seems to be a distant echo on the horizon. Let’s hope it is not your next threat!

Pierre-Martin Tardif is a member of the ISACA Emerging Trends Working Group. A longstanding IT and cyber security professional and educator, he is based in Quebec, Canada.

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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.”

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Overcoming the cyber paradox: Shrinking budgets – growing threats

Recent years have seen a general cost-cutting in organisations caused by economic pressures. Many organisations have seen a fall in customer demand due to the cost-of-living crisis, as well as inflationary pressures affecting costs. Higher interest rates, increasing organisations’ cost of capital, are another factor.

There’s also a sense of fatigue associated with spending on cyber security. Businesses’ spending on cyber has been increasing year-on-year for a sustained period of time, and a tendency has crept in for organisations to feel that, by now, they have done the necessary investing required to protect themselves, even though the reality is that the cyber threat landscape is ever-intensifying and regulatory pressures are mounting.

Lastly, we’ve seen a ‘platformisation’ of cyber software, with the big suppliers creating cohesive, unified cyber solutions. This encourages CISOs to embrace economies of scale in their spending, allowing them to do ‘more with less’. This has led to reductions in spending on single-use-case software solutions.

All of these factors combined are contributing to a flatlining of cyber budgets over the past 12 to 18 months in many organisations.

What makes organisations feel security is a worthwhile ‘cut’?

In this area, spending is highly correlated to compliance – often more than risk appetite. Compliance drives action, and this leads to a situation where if the organisation feels compliance has been achieved, the spend begins to plateau as the sense of urgency around cyber dissipates.

Some sectors are pushing hard on compliance, for example DORA for financial services in EMEIA and NIS2 for critical infrastructure in the European Union (EU). Spending on cyber security is more robust in these sectors, commensurate with the demands of these regulatory frameworks, but in sectors where regulation is less onerous, the spend is measurably flattening.

How can CISOs and security leaders lobby to maintain their budgets?

This is where a shift in perspective is badly needed. The case needs to be made that spending on cyber is a value investment – not just a risk management cost. Organisations need to start regarding cyber as an enabling ecosystem which unlocks value in multiple ways. It can enable AI implementation right across the organisation, for one thing. It can help enable acquisitions, for another. Creating a strong platform can also differentiate the organisation in the eyes of customers. All this contributes tangible value.

This is an important shift in mindset, from a perspective that views cyber only as a cost to one that understands it as an enabling infrastructure that links directly to the value generated by the products and services it underpins.

This new perspective should enable businesses to consider that, instead of relying solely on central funding for cyber, they can allocate to cyber a share of their budgets for new initiatives – on the basis that an optimal cyber infrastructure is a necessary condition of the initiative’s success.

It’s also useful to quantify the effectiveness of cyber spend, using Cyber Risk Quantification to demonstrate the tangible link between risk reduction and spend.

How can CISOs and security leaders increase their budgets?

One of the main things cyber can enable is AI, and this is becoming the fastest-moving – and fastest-growing – change catalyst in the whole landscape. There is no doubt that AI is a cyber threat multiplier, allowing cyber criminals to become better at what they do: better malware, better phishing, and so on.

This means that the custodians of business need to become better, too. And that’s going to require ongoing investment, and an ongoing evolution of the tools and solutions we implement, to enable organisations to try and keep up with the criminals.

As cyber criminals avail themselves of AI to create more effective cyber-attacks, organisations are going to need to fight AI with AI.  It is important to look at opportunities to automate cyber defence, especially in key use cases around Threat Detection and Response, Automated Testing and User Access Rights management. 

EY’s research shows that one of the key indicators of organisations who perform best in cyber security is that they consistently adopt emerging technology – especially automation – quickly. Companies who can ingrain that technology-friendly approach are the ones that suffer the least from being attacked.

The threat outlook for 2025

The existing big threats – ransomware, phishing and supply chain attacks – will all continue, and will continue to grow in sophistication. Alongside that, we expect to see more targeting of Operational Technology (OT), as well as the Internet of Things (IoT).

It’s reasonable to expect that the fast growth of AI implementation across organisations and sectors will produce new vulnerabilities, and that as a result, more data breaches will occur as an inevitable aspect of this fast pace of change.

Finally, the other key development will be the way cyber criminals are themselves utilising and deploying AI. The intensity of malware attacks is likely to increase, as attackers weaponise GenAI. The pace of development is capable of being equally effective on both sides of the battle, which is precisely why organisations cannot afford to be complacent.

Richard Watson is global and APAC cyber security consulting lead at EY

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