Four years into the new AI era, and few business leaders appear happy with the results.
At issue is growing impatience with IT leaders who have not moved their organizations beyond using AI for small tweaks to current business process.
Seventy-seven percent of business decision-makers, including C-suite leaders, directors, and managers, believe their organizations are dedicating too much of their AI investments to incremental improvements, according to a survey commissioned by Microsoft-focused IT advisory services provider Avanade.
Only 11% of decision-makers expect AI to fundamentally change how their organizations operate, create value, or compete in the next year. Nearly two-thirds say AI has not yet delivered returns that justify their investment and effort, and three-quarters believe their organizations have overstated their AI maturity.
The survey shows that many organizations — and their CIOs — aren’t yet embracing the potential of AI, even though they see the possibilities, says Ben Beath, Avanade’s chief AI officer.
“Confidence is high, but confidence isn’t the same as change,” he adds. “Having Copilot licenses and a few dozen use cases can feel to a leader like maturity, but it probably isn’t if it hasn’t changed the way the work is actually getting done.”
When business leaders don’t see major returns from their AI investments, it suggests their organizations still haven’t reached AI maturity, he says, likely due to a misguided AI strategy and approach.
“That’s the product of bolting AI onto either broken or legacy processes,” he adds. “You just get a faster legacy process.”
Is your AI strategy transformational enough?
Instead of looking at ways to reinvent their businesses through AI, many IT leaders are chasing tools that summarize email messages or generate basic reports, Beath suggests. The basic uses of AI can significantly improve employee productivity, but they won’t transform the organization, he adds.
“Leaders aren’t confused about this,” he says. “They can see they’re stuck in efficiency and productivity mode when it comes to AI. The issue isn’t awareness; it’s that incremental projects are easier to approve, they’re easier to measure, and they’re a lot less risky for whoever sponsors them.”
But to be truly transformational, AI needs fully integrated into the business instead of bolted on to existing processes, he adds. And leading CIOs are doing just that, reimagining their organizations’ business processes to reap AI’s true benefits.
“The clients that are building AI into their business aren’t thinking about how they can add AI incrementally on top of an existing workflow,” he explains. “They’re saying, ‘What would this process in our business look like if it was reimagined with AI?’ and AI is embedded in every step of the way.”
Leadership gap
As Beath sees it, the majority of organizations are suffering from a leadership crisis, leaving CIOs to pursue AI projects without a broader leadership coalition getting involved.
“This is a leadership conversation and it’s not just an IT one,” he adds. “If AI strategy sits only with the CIO, there’s more of a focus on efficiency. If it sits with the CEO or the CFO and business leaders working in partnership with the CIO, you get AI transformation.”
CIOs, working with other business leaders, shouldn’t ask where they can use AI, but what business they would build today if they started from scratch with AI, Beath advises.
Not all CIOs spearheading AI strategies are focused solely on incremental gains. According to CIO.com’s State of the CIO survey, 59% of IT leaders report that some or most of their AI initiatives have met or exceeded ROI goals, with some even bringing AI transformation home to IT workflows.
But if more IT leaders focus on these more transformational uses of AI, rather than siloed efficiencies, they can turn the tide at their own organizations, bringing greater AI maturity and better business results, Beath adds.
“It’s not because the models are bad or because the pilots are poorly selected; it’s because the hard parts of AI are where data meets the app, or where technology meets the process, or where it meets the business,” he says. “AI transformation needs someone thinking across all of those, not just focused on the tech piece.”
Not an either-or proposition
CIOs may miss out on AI’s potential if they focus on incremental initiatives instead of transformational projects, but they don’t have to choose one or the other. In fact, many IT leaders, such as Ed Keisling, chief AI officer at Progress Software, believe the key to advancing the organization is using AI for both.
“I believe they go hand in hand,” he says. “The incremental improvements allow organizations to begin to explore the art of the possible with AI, and in some instances, can compound across an entire workflow to bring transformational results.”
The company is using AI agents, for example, to synthesize updates from its workplace collaboration, project management, and knowledge management systems to generate updates for leadership. Its sales organization also uses agents to synthesize data from the company’s CRM, data platforms, and customer systems to generate quotes more quickly and accurately, he says.
Progress Software is also deploying AI for more transformational purposes, including how the company handles requests for information and requests for proposals.
“These are extremely time-consuming processes that used to take days and now can be completed in minutes,” Keisling says. “It allows us to be more responsive to opportunities.”
Still, scaling AI tools across the organization can be tricky, he adds. In addition, several issues, including data sovereignty, security, and cost, hold organizations back from more transformational AI use cases, he says.
“Theres still a big challenge in scaling AI tooling from the individual to a team, and then to a team of teams or an organization,” Keisling says. “A lot of this has to do with how organizations want to manage the risk — which could be the risk of inaction as much as the risk of action — against the opportunities and threats that they perceive in the market.”
Meanwhile, the continuing elusiveness of AI ROI means IT leaders must be hyper focused on budgets and results, he adds. However, ROI doesn’t come only from transformational projects.
“If AI takes meaningful time out of a high-volume workflow, increases throughput, improves quality, or frees capacity, that can create significant economic value without being labeled ‘transformational,’” Keisling says.
Start small and build
Digital adoption software provider WalkMe has also found both incremental and transformational uses for AI, says Tal Carmi, the CIO there. The company started with incremental uses but is evolving as it goes, he adds.
“Incremental improvements are the steppingstones to transformation,” he says. “We have some areas where we started with AI-based solutions such as Copilot and after seeing the success rate, they evolved into auto pilot, transforming how work is done.”
Still, WalkMe has more work to do before most of its AI uses are transformational, Carmi says.
“In some areas, we’re already there and in others, we are not there yet,” he adds. “What’s holding us back is a combination of systems limitations, processes involving face to face interactions, risk ownership, and employee enablement.”
Many organizations appear to be held back by issues that plagued them before they had AI, he suggests.
“AI only magnifies your knowledge and data problems,” Carmi says. “Telling your LLM to extract data and build a dashboard is easy, making sure it extracts the right data and processes it the right way is a different story.”
Legacy systems also create roadblocks, he adds. “Many of the systems people most want to automate don’t have an API and are unlikely to get one anytime soon,” he says. “So people improvise, and that’s how shadow IT gets in.”