Predictions for 2025: How AI’s real world value will come to life

Why 2025 is a make or break year for AI adoption and deployment, and what CEOs need to consider to capture value from this transformational technology

The AI and data landscape are changing at an exponential rate, and transforming industries across every sector. While AI hype has dominated our attention for the past few years, 2025 will mark an important shift for this transformational technology: it’s the year we focus on its utility, not just its promise. 

As we look to the year ahead, I’d like to give you a preview into my predictions for 2025:

This is the year of AI utility

For years, AI’s promise has been loud and clear. Now, the adoption curve is steepening, and companies across industries are deploying AI where it has proven reliability. It’s a defining moment: those who integrate AI thoughtfully will drive efficiencies that free up resources for critical tasks, making 2025 an “adapt or die” year for organizations. AI can streamline workflows, unlock previously inaccessible insights, remove intermediaries and more. Businesses that implement AI strategically will see a measurable impact in the hours of work reduced, millions of dollars saved, and accelerated pace of innovation.

Through this shift, AI is not the “what,” but the “how.” It represents how we extract deeper insights and produce better outcomes from our data. It is how we create more value for our business, our workers, and our customers. We are moving beyond the question of “What can the technology do?” and towards  “How can we best use this technology to help us achieve our goals?” 

Proven AI capabilities like document synthesis, automation, and predictive analysis are ready to work in sectors from finance to healthcare, but to capture this value, leaders must approach AI with a mindset rooted in utility, reliability, and a relentless drive to understand how it fits into their business.Going forward, AI investments will face the same kind of rational scrutiny and value expectations of any technological expenditure. 

Everyone is now a data user

As a part of this transition to utility, AI has changed the game in that everyone is now a data user. Generative AI has made data and data analysis instantly accessible via conversational language, and that will change professional roles across the board. Business intelligence, once a specialized function, is now being democratized. Professionals from all backgrounds are tapping into data-driven insights, and as users gain comfort with AI, data roles will evolve. CEOs must anticipate this evolution, investing in upskilling initiatives and aligning roles with AI’s capabilities, ensuring that every employee is equipped to contribute to a data-centric organization.

McKinsey recently estimated that by 2030, 30% of the work done across the U.S. economy could be automated, a trend that AI will only accelerate. As job postings requiring generative AI skills surge, CEOs must prioritize reskilling and equipping their teams with the tools and training necessary to leverage AI effectively, and importantly, redefine their incentive structures. As outputs can become automated, employee incentives must be refocused on strategic work, problem-solving, and adoption of new capabilities to drive results. The future workforce will thrive on versatility and adaptability, so leaders must plan accordingly to meet the moment.

AI transparency and reliability is reliant on industry leadership 

The tech industry will shoulder much of the responsibility of ensuring that AI is used in positive, ethical ways. Voices will call for guidelines, guard rails and regulation, and all will be necessary. But AI development moves amazingly fast, while regulatory bodies take a calculated, measured pace. And they don’t always move in the same direction at the same time; think of how differently data privacy has been approached by the European Union, the United States and the State of California. 

Thus, we need to see the industry take the lead on ensuring safe use of AI by mitigating bias, reducing errors, improving transparency, and promoting proper uses. As an industry, we need to think about the best ways to promote accuracy, or provide clarity when “hallucinations” or inaccuracies may occur. Regulatory approaches need to be crafted carefully, and it’s important that the industry participate to help shape rules that protect consumers and allow technological progress to continue in the right direction.

AI success requires curiosity

This AI revolution calls for a new kind of leadership: one driven by an unrelenting curiosity. As CEOs, it’s not enough to delegate AI initiatives; we must personally dive into the possibilities, learn the intricacies, and actively engage with the technology. Our collective curiosity will lead us to new applications, help us spot risks, and enable us to shape AI’s trajectory in ways that truly benefit our organizations. 

Curiosity is the foundation of innovation, and when leaders take the time to learn about AI’s evolving landscape, it inspires the entire organization to do the same. This collective curiosity will propel our industries forward and help us avoid the trap of underestimating AI’s future impact.

The path AI is on today echoes the rise of mobile technology. Just as we don’t consciously choose to “use a phone” anymore, AI will become so integrated that it will simply be a natural part of how we work and live. We may not yet be able to fully predict the applications that will emerge, but we know the shift will be profound, affecting everything from how we interact with data to how we organize our businesses.

As we embark on this year, we have to start with a steady drumbeat of taking what works, deploying, expanding, testing and learning. And together, we must remain clear-eyed toward both the immediate potential and the long-term transformation ahead. Onwards!