Every Company Wants an AI story to tell
Billions of dollars are being committed to AI pilot programs, proofs of concept, and innovation initiatives to keep pace with a changing world. Yet as AI moves from buzzword to budget line, a clear gap is emerging between what leaders say they want to do (and spend) and what they actually do.
The early promise of AI is no longer speculative. Across industries, organizations are seeing measurable productivity gains and financial impact. According to EY research, including the EY US AI Pulse Survey, 96 percent of senior leaders whose organizations are investing in AI report productivity gains over the past year. More than half (56 percent) say those investments are delivering positive returns on their investment.
But when it comes to follow-through, ambition often outpaces reality. A year ago, 65 percent of leaders expected their organizations to invest at least $1 million in AI. Today, only 58 percent say that happened. Among those predicting big bets—$10 million or more—the gap is even wider: Thirty-four percent forecasted that level of investment, but just 23 percent followed through.
“This is the paradox of AI transformation,” says Dan Diasio, EY global consulting AI leader. “Organizations are convinced of the technology’s potential and they are seeing results, but their investment strategies haven’t caught up. The winners will be those who scale deliberately—not experimentally.”
The data suggests a simple truth: AI maturity is no longer determined by enthusiasm but by mindset and execution. Companies investing at scale with the mindset of reimagining their business are pulling ahead. Seventy-one percent of organizations spending $10 million or more across business units report significant productivity gains, compared with just over half (52 percent) of those investing less.
In other words, AI’s advantage compounds with commitment. The path to transformation isn’t about experimenting, but reinventing all aspects of business, from systems of records to intelligence, the workforce to the customer with AI. At Ernst & Young LLP, the EY Consulting practice has announced their EY.ai Value Blueprints, a methodology and accelerator to re-architect the entire organization towards value creation in the age of AI.
Forming AI-First Principles
Order-to-cash. Inside sales. Product innovation. These types of workflows tend to involve multiple teams collaborating with different parts of an organization, handing off work from one person to the next in a set system. These processes involve many steps, meaning these are natural areas where AI can enable productivity gains and cost savings—and that’s what most companies will do. But doing so misses AI’s true advantage. These are the workflows that AI can help reinvent entirely.
“Cross-functional scenarios are great opportunities for focusing on what the objective of the entire process was originally meant to be,” Diasio says. “You can then begin to reimagine it.”
The word “reimagine” is key. Diasio and his team at EY Consulting work with organizations to help them unlock value with AI through a process called EY.ai Value Blueprints. There are several key aspects to this approach, including assessing a company’s organizational and tech readiness, identifying an AI value map, and exploring new business models.
First, however, Diasio says executives need to transition to a business approach that prioritizes mindset and skill set over simply updated toolsets. By shifting this focus, organizations can begin to more clearly target growth, rather than just savings.
“This framework is helpful because clients tend to think of this as a technology implementation,” Diasio says. “Really, it’s a business transformation.”
Once it does come time to look at workflows, Diasio often encourages clients to focus on two steps: the input and the output. Once they do that, he and his team can help reinvent everything in between from the ground up. They map all steps to a taxonomy of agents that can do the work with some level of autonomy, discovering new jobs or controls to create along the way. Finally, the company can use this faster way of working to create entirely new approaches for business. All of this is often first tested within an internal AI native business unit, allowing data engineers to perfect the process before it’s launched more widely.
“AI agents do the majority of work,” Diasio says. “We look at a cluster of steps, figure out which type of agent can do them, and then agents are talking to each other and it’s nothing like the process that was built before. It’s not identifying and optimizing existing steps. It’s reinventing an entirely new process that maybe takes 56 steps down to 14 and 45 hours down to 45 minutes.”
In product innovation, for instance, the process begins with collecting consumer insights, discovering unmet needs, and then creating a new product to fit that space. Ordinarily, the back-and-forth and testing involved in this workflow can take 18 months to create a new product. Using AI, however, the EY.ai Value Blueprints process begins with the same first step, but then creates a range of different options, tests them virtually with personas, gains feedback, and produces a product within weeks. Using this process, a company not only expedites its product innovation, but can also devote its human talent to creating new opportunities.
“A consumer product company we work with has found new ways to do licensing agreements that reshaped their revenue for growth in a manner that wasn’t humanly possible before,” Diasio says. “Another client is now expanding into more geographies. It opens up bandwidth.”
Creating New Jobs for the Future
Reinventing work means reinventing jobs—in a good way.
The traditional approach to incorporating AI hasn’t yielded benefits because it doesn’t save that much time. When companies simply use AI to automate existing tasks and then take time to fact-check that automation, it doesn’t save hours or lead to new profits or breakthroughs. But when the entire workflow is reinvented and optimized for AI agents, the humans overseeing the work wind up having more time to think creatively about innovation.
“We found that 83 percent of workers were enthusiastic about agentic AI making their work better,” Diasio says. “When we redesign the process, we establish that people are specifically placed to do the parts of the job that are more creative and purposeful. Instead of asking someone to do something new on top of their old job, we just reinvent their job—which also helps upskill them for the future.”
Ultimately, the EY.ai Value Blueprints process leads to new ROI—the type that can scale companies. Instead of introducing 10 new products a year, a company can launch a thousand variations of the same product that are each targeted to a specific audience and region, all without spending more on research and production. “We typically work with clients for four weeks to help them figure out how to optimize value and create a sustainable competitive advantage,” Diasio says. “The process can end up actually meaning they hire even more workers.”
In the end, EY.ai Value Blueprints unlocks human creativity—and returns—in entirely new ways.
“Often there is this narrative that AI will start to commoditize knowledge workers,” Diasio says. “And one thing that we find in this space is that the knowledge, experience, and creativity of people are actually what creates a durable competitive advantage. AI just means you can accomplish things a lot faster—but it’s the people who will then raise the bar to create something truly original and drive value.”
The views reflected in this article are the views of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.
