Generative AI Surpasses Cybersecurity as Top Tech Budget Priority for 2025, AWS Study Reveals

Generative AI tops cybersecurity in 2025 tech budget priorities, new AWS study finds

Generative AI will surpass cybersecurity in many corporate tech budgets this year -- with 45% of global IT leaders naming it their top spending priority for 2025, according to a new report commissioned by Amazon Web Services. That finding from the inaugural AWS Generative AI Adoption Index, released Tuesday morning, "made me step back and think," acknowledged Rahul Pathak, AWS VP of Data & AI Go-to-Market, in an interview about the survey results. Pathak said he interpreted the finding not as a sign that organizations view AI as more important than security, but as an indication of AI's growing impact on business. Within AI projects, he noted, security is also a top concern, including data protection and responsible AI use. The study, conducted by Access Partnership, is based on a global survey of 3,739 senior IT decision-makers across nine countries, including the U.S., U.K., Germany, Japan, and India. The study found that 90% of organizations are already using generative AI tools in some capacity, with nearly half moving beyond experimentation to full integration. "AI is rapidly, rapidly being adopted," Pathak said. "The fact that nine out of 10 folks are looking at this actively and putting it into play -- you can't afford to wait around." Amazon's cloud unit is heavily invested in AI technologies including its Bedrock platform for AI models. Asked about potential skepticism from the findings aligning conveniently with AWS's business interests, Pathak emphasized the independence of the survey and the wide range of global respondents. "It's not us saying it -- it's nearly 4,000 IT leaders around the world," he said. "If you don't believe us, listen to them." More findings from the study:

Gen AI spending now higher than security investment for many businesses

Spending on generative AI has surpassed cybersecurity, with financial services, ICT, manufacturing and retail all looking to adopt the technology, new research has claimed. As a result, three in five organizations have now appointed a Chief AI Officer (CAIO) or similar to oversee their strategy, the latest Generative AI Adoption Index from cloud computing giant AWS found. According to the report, almost all (90%) organizations are using GenAI in some capacity, with 44% already having moved from experimentation to full implementation. AWS's report explores the different ways companies are planning to go about deploying AI, with half as many companies again planning to build their own custom apps using existing models (58%) as those using off-the-shelf tools (40%). An equally high number of businesses will also use fine-tuned models based on their own proprietary data. (55%), but on the whole, a hybrid of building and buying AI tools appears to be favored. Over half (56%) or the companies surveyed also noted that they already have internal AI training programs, but that figure is expected to jump by 19 percentage points to 75% by the end of 2025. However, with constrained budgets and uncertainty about how to go about defining precise AI skillsets, it's clear that companies will be spending time finding their feet before workers might feel fully supported. Still, 92% of companies are requiring AI skills during recruitment in 2025, demonstrating a huge opportunity for workers to upskill and prepare for an evolving workplace. An additional one in four (26%) also plan to adopt more AI over the next year, showing how leadership roles are developing to handle AI as well as humans - a sentiment felt by Salesforce CEO Marc Benioff, who believes the current and next generations of CEOs will need to manage AI agents alongside humans.

AWS report: Generative AI overtakes security in global tech budgets for 2025

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Generative AI tools have surpassed cybersecurity as the top budget priority for global IT leaders heading into 2025, according to a comprehensive new study released today by Amazon Web Services. The AWS Generative AI Adoption Index, which surveyed 3,739 senior IT decision makers across nine countries, reveals that 45% of organizations plan to prioritize generative AI spending over traditional IT investments like security tools (30%) -- a significant shift in corporate technology strategies as businesses race to capitalize on AI's transformative potential. "I don't think it's cause for concern," said Rahul Pathak, Vice President of Generative AI and AI/ML Go-to-Market at AWS, in an exclusive interview with VentureBeat. "The way I interpret that is that customers' security remains a massive priority. What we're seeing with AI being such a major item from a budget prioritization perspective is that customers are seeing so many use cases for AI. It's really that there's a broad need to accelerate adoption of AI that's driving that particular outcome." The extensive survey, conducted across the United States, Brazil, Canada, France, Germany, India, Japan, South Korea, and the United Kingdom, shows that generative AI adoption has reached a critical inflection point, with 90% of organizations now deploying these technologies in some capacity. More tellingly, 44% have already moved beyond the experimental phase into production deployment. 60% of companies have already appointed Chief AI Officers as C-suite transforms for the AI era As AI initiatives scale across organizations, new leadership structures are emerging to manage the complexity. The report found that 60% of organizations have already appointed a dedicated AI executive, such as a Chief AI Officer (CAIO), with another 26% planning to do so by 2026. This executive-level commitment reflects growing recognition of AI's strategic importance, though the study notes that nearly one-quarter of organizations will still lack formal AI transformation strategies by 2026, suggesting potential challenges in change management. "A thoughtful change management strategy will be critical," the report emphasizes. "The ideal strategy should address operating model changes, data management practices, talent pipelines, and scaling strategies." Companies average 45 AI experiments but only 20 will reach users in 2025: the production gap challenge Organizations conducted an average of 45 AI experiments in 2024, but only about 20 are expected to reach end users by 2025, highlighting persistent implementation challenges. "For me to see over 40% going into production for something that's relatively new, I actually think is pretty rapid and high success rate from an adoption perspective," Pathak noted. "That said, I think customers are absolutely using AI in production at scale, and I think we want to obviously see that continue to accelerate." The report identified talent shortages as the primary barrier to transitioning experiments into production, with 55% of respondents citing the lack of a skilled generative AI workforce as their biggest challenge. "I'd say another big piece that's an unlock to getting into production successfully is customers really working backwards from what business objectives they're trying to drive, and then also understanding how will AI interact with their data," Pathak told VentureBeat. "It's really when you combine the unique insights you have about your business and your customers with AI that you can drive a differentiated business outcome." 92% of organizations will hire AI talent in 2025 while 75% implement training to bridge skills gap To address the skills gap, organizations are pursuing dual strategies of internal training and external recruitment. The survey found that 56% of organizations have already developed generative AI training plans, with another 19% planning to do so by the end of 2025. "For me, it's clear that it's top of mind for customers," Pathak said regarding the talent shortage. "It's, how do we make sure that we bring our teams along and employees along and get them to a place where they're able to maximize the opportunity." Rather than specific technical skills, Pathak emphasized adaptability: "I think it's more about, can you commit to sort of learning how to use AI tools so you can build them into your day-to-day workflow and keep that agility? I think that mental agility will be important for all of us." The talent push extends beyond training to aggressive hiring, with 92% of organizations planning to recruit for roles requiring generative AI expertise in 2025. In a quarter of organizations, at least 50% of new positions will require these skills. Financial services joins hybrid AI revolution: only 25% of companies building solutions from scratch The long-running debate over whether to build proprietary AI solutions or leverage existing models appears to be resolving in favor of a hybrid approach. Only 25% of organizations plan to deploy solutions developed in-house from scratch, while 58% intend to build custom applications on pre-existing models and 55% will develop applications on fine-tuned models. This represents a notable shift for industries traditionally known for custom development. The report found that 44% of financial services firms plan to use out-of-the-box solutions -- a departure from their historical preference for proprietary systems. "Many select customers are still building their own models," Pathak explained. "That being said, I think there's so much capability and investment that's gone into core foundation models that there are excellent starting points, and we've worked really hard to make sure customers can be confident that their data is protected. Nothing leaks into the models. Anything they do for fine-tuning or customization is private and remains their IP." He added that companies can still leverage their proprietary knowledge while using existing foundation models: "Customers realize that they can get the benefits of their proprietary understanding of the world with things like RAG [Retrieval-Augmented Generation] and customization and fine-tuning and model distillation." India leads global AI adoption at 64% with South Korea following at 54%, outpacing Western markets While generative AI investment is a global trend, the study revealed regional variations in adoption rates. The U.S. showed 44% of organizations prioritizing generative AI investments, aligning with the global average of 45%, but India (64%) and South Korea (54%) demonstrated significantly higher rates. "We are seeing massive adoption around the world," Pathak observed. "I thought it was interesting that there was a relatively high amount of consistency on the global side. I think we did see in our respondents that, if you squint at it, I think we've seen India maybe slightly ahead, other parts slightly behind the average, and then kind of the U.S. right on line." 65% of organizations will rely on third-party vendors to accelerate AI implementation in 2025 As organizations navigate the complex AI landscape, they increasingly rely on external expertise. The report found that 65% of organizations will depend on third-party vendors to some extent in 2025, with 15% planning to rely solely on vendors and 50% adopting a mixed approach combining in-house teams and external partners. "For us, it's very much an 'and' type of relationship," Pathak said of AWS's approach to supporting both custom and pre-built solutions. "We want to meet customers where they are. We've got a huge partner ecosystem we've invested in from a model provider perspective, so Anthropic and Meta, Stability, Cohere, etc. We've got a big partner ecosystem of ISVs. We've got a big partner ecosystem of service providers and system integrators." The imperative to act now or risk being left behind For organizations still hesitant to embrace generative AI, Pathak offered a stark warning: "I really think customers should be leaning in, or they're going to risk getting left behind by their peers who are. The gains that AI can provide are real and significant." He emphasized the accelerating pace of innovation in the field: "The rate of change and the rate of improvement of AI technology and the rate of the reduction of things like the cost of inference are significant and will continue to be rapid. Things that seem impossible today will seem like old news in probably just three to six months." This sentiment is echoed in the widespread adoption across sectors. "We see such a rapid, such a mass breadth of adoption," Pathak noted. "Regulated industries, financial services, healthcare, we see governments, large enterprise, startups. The current crop of startups is almost exclusively AI-driven." The business-first approach to AI success The AWS report paints a portrait of generative AI's rapid evolution from cutting-edge experiment to fundamental business infrastructure. As organizations shift budget priorities, restructure leadership teams, and race to secure AI talent, the data suggests we've reached a decisive tipping point in enterprise AI adoption. Yet amid the technological gold rush, the most successful implementations will likely come from organizations that maintain a relentless focus on business outcomes rather than technological novelty. As Pathak emphasized, "AI is a powerful tool, but you got to start with your business objective. What are you trying to accomplish as an organization?" In the end, the companies that thrive won't necessarily be those with the biggest AI budgets or the most advanced models, but those that most effectively harness AI to solve real business problems with their unique data assets. In this new competitive landscape, the question is no longer whether to adopt AI, but how quickly organizations can transform AI experiments into tangible business advantage before their competitors do.