What must enterprises do to be AI ready?
Businesses can scale AI by modernising their data, building secure platforms and empowering their people.
The last few years have brought a surge of interest in artificial intelligence. A host of AI-enabled tools and applications are now available to enterprises, many of them driven by generative AI (genAI) technology.
Four cornerstones for a winning AI PC strategy
The ability to successfully implement artificial intelligence (AI) and deliver impact is likely to be a defining factor of enterprise success in the near term.
Personalised customer experiences that uplift sales, far higher employee productivity and workforces geared toward innovation rather than bureaucracy are among the game- changing opportunities businesses will be striving for.
But achieving this requires carefully crafted technological foundations that are optimised toward the needs of AI.
Foundry’s AI Priorities Study 2025 shows that over half of businesses are increasing AI investment (53%), trying to build their AI capability with learning platforms (38%) and increasing data investments (37%) among other things.1
But businesses know AI success needs modernisation. For nearly a third of businesses (31%), the business objective driving cloud investment was acceleration of AI adoption or machine learning.2
As with early waves of digital transformation, success will come to businesses that move fast and understand that ad hoc adoption will not succeed. AI will only deliver its full promise if businesses can take it to scale.
Barry Cooks, VP of Technology at Amazon, comments: “At AWS, we’re also seeing a transformation across the technology landscape as organisations move from experimental AI projects to production deployments at scale. This shift demands infrastructure that can deliver unprecedented performance while maintaining security, reliability and cost-effectiveness.”3
In this eBook, we will explore the various elements that must be brought together for an organisation to be AI ready.
The proportion of businesses reporting AI use jumped to 78% last year, up from 55% in 2023.4
49% of technology leaders say that AI is “fully integrated” into their companies’ core business strategy.5
Just 4% of CFOs report having a conservative AI strategy; a third have adopted an aggressive approach.6
Before businesses can realise the full value of AI, they need to build a strong data foundation. However, as research from DATAVIERSITY shows, even as organisations accelerate their adoption of generative AI (genAI) and automation, many are unintentionally restricting their data.7 According to its study, data silos are the top concern for 68% of business leaders in 2025, up 7% from the previous year.8
Building accurate AI models requires breaking down these silos and replacing them with a modern, scalable and secure infrastructure where data can be accessed, governed and analysed in real time.
In practice, this means investing in cloud-based data lakes and warehouses that can handle high volumes and diverse data formats while ensuring they’re integrated with data governance frameworks. Data quality, lineage and security must be treated as priorities, especially when deploying genAI models trained on enterprise content.
Case study: New York Life
New York Life modernised its legacy data systems by migrating from Apache Hadoop to a unified, cloud-based platform on AWS. The transformation improved access to high-quality data across the business while strengthening governance, compliance and lineage tracking, helping the insurer to realise the full potential of its data and power next-generation AI applications.
With the data foundation in place, organisations can consider how best to build an environment where AI solutions can be designed, tested, deployed and scaled successfully.
According to Flexential’s 2025 State of AI Infrastructure report, 44% of IT leaders report that infrastructure constraints are the top barrier to expanding AI initiatives.9 Putting in place technologies that can support the requisite performance, cost and security considerations is therefore key.
To be fit for purpose, a modern cloud-enabled AI platform should be able to support the full life cycle of model development while embedding governance, monitoring and automation at every stage. This requires providing teams with scalable compute power, access to trusted models and the tools to integrate both open source and proprietary approaches. Security and compliance controls must be implemented from the start, ensuring sensitive data and intellectual property remain protected even as usage grows.
Case study: Simplismart.ai
India-based startup Simplismart.ai helps enterprises deploy high-performance genAI workloads. To meet surging enterprise demand, the company worked with AWS to implement intelligent autoscaling and streamline infrastructure across cloud and hybrid environments. As a result, Simplismart.ai reduced infrastructure costs by 40%, scaled operations sixfold in six months and achieved an 8× increase in GPU hours deployed.
The technical challenge aside, organisations will also need to deal with a major cultural shift within the workplace. Many employees are concerned about what AI means for their futures. Research from the UK’s Trades Union Congress, for example, found that half of adults in the country are concerned about the impact of AI on their jobs.10
As businesses ramp up their AI programmes, they will therefore also need to invest in focused training and skills development so that workers see AI as a tool to enhance their work, not replace it. Cloud providers can help with this task. AWS, for instance, provides a range of training programmes and certification schemes.
Embedding AI into business processes is equally critical. Rather than confining AI to isolated projects or applications, organisations should look to weave it into core workflows such as customer engagement, supply chain, product design and decision-making. That involves creating user-friendly interfaces, integrating AI into existing applications and empowering teams to experiment with genAI tools safely and responsibly.
As AI becomes ever more critical to business success, organisations need to redouble their efforts on modernising data, scaling their platforms and empowering their people with embedded AI workflows. Businesses that act decisively now will be better able to scale pilots and place AI at their heart of their business, giving them a significant lead as businesses continue to transform.
Case Study: Accelya
Accelya, a global leader in airline software, powers more than 200 airlines on AWS to process over 30 billion offers daily. By integrating AWS generative AI through Amazon Q Apps, the company streamlined its testing processes, cutting test case generation effort by 70-80%. This efficiency increase enables Accelya to deliver innovative solutions to customers faster.
Endnotes
1 Foundry, AI Priorities Study, 2025, https://foundryco.com/tools-for-marketers/research-ai-priorities/
2 Foundry Cloud Computing Study, https://resources.foundryco.com/download/cloud-computing-executive-summary
3 AWS, Powering innovation at scale: How AWS is tackling AI infrastructure challenges, 2025, https://aws.amazon.com/blogs/machine-learning/powering-innovation-at-scale-how-aws-is-tackling-ai-infrastructure-challenges/
4 HAI, AI Index Report 2025, 2024, https://hai.stanford.edu/ai-index/2025-ai-index-report/economy
5 PwC, 2025 AI Business Predictions, 2024, https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html
6 Salesforce, From Caution to Core Strategy: New Study Shows CFOs Going All In on AI, 2025, https://www.salesforce.com/news/stories/cfos-invest-ai-for-growth/
7 DATAVERSITY, Data Strategy Trends in 2025: From Silos to Unified Enterprise Value, 2024, https://www.dataversity.net/articles/data-strategy-trends-in-2025-from-silos-to-unified-enterprise-value/
8 Ibid
9 Flexential, 2025 State of AI Infrastructure Report, 2025, https://www.flexential.com/resources/report/2025-state-ai-infrastructure
10 The Guardian, Half of UK adults worry that AI will take or alter their job, poll finds, 2025, https://www.theguardian.com/technology/2025/aug/27/half-of-uk-adults-worry-that-ai-will-take-or-alter-their-job-poll-finds
