With AI copilots and generative AI tools becoming deeply embedded in enterprise workflows, companies face a mounting challenge: managing too many assistants and too little strategy. According to Ofir Bloch, WalkMe VP of Strategic Positioning. CIOs must now act as orchestrators of AI technologies—balancing usability, security, and governance in a fast-evolving environment.
A recent report from Wiz projects that 85% of enterprises will use AI agents by 2025, as the market for AI assistants balloons from $3.7 billion in 2023 to $150 billion in 2025. However, most businesses are rolling out these tools without considering their operational impact, creating environments where employees interact with multiple AI agents—each potentially offering conflicting advice.
WalkMe’s own research shows that the average enterprise employee now uses three different AI assistants every week. Without coordination, this risks not just confusion, but strategic misalignment, duplicated tasks, and wasted investment.
User Experience, Not Just Deployment, Will Define AI Transformation Success
“Technology transformation is about people first,” says Bloch. “The one constant in this fast-changing environment is the end user. If they can’t make sense of the tools, or if the tools contradict each other, AI adoption will stall.”
He warns that copilot overload is a growing risk. As AI assistants are integrated across various tools—like CRM, productivity suites, and analytics platforms—employees may face conflicting prompts or redundant suggestions. Worse, some AI-generated recommendations could clash with internal policies or compliance frameworks.
To mitigate these issues, CIOs must define clear usage policies, streamline user experiences, and ensure employees know which AI tools to trust—and when. Ideally, Bloch explains, users shouldn’t even realize when they’ve switched between copilots.
“Without strong coordination and oversight,” he says, “multiple AI agents could end up doing more harm than good.”
CIOs also face another wave of transformation: the rise of citizen developers. With generative AI enabling non-technical users to build applications via simple prompts, enterprise IT must shift from gatekeepers to enablers with guardrails. This “prompt-to-app” evolution brings agility—but also risks related to security, compatibility, and technical debt.
“It’s a thrilling shift,” Bloch says, “but businesses must stay ahead of the risks. Just because someone can build a tool in hours doesn’t mean it will behave well with enterprise systems or protect sensitive data.”
From Text to Action: Unlocking the Next Era of Enterprise AI
Bloch also points to a broader shift: moving from text-to-text use cases, where AI generates copy or summaries, to text-to-action, where AI can trigger automated workflows from a simple prompt. This shift, he believes, will define the next phase of enterprise productivity.
“Businesses will start using AI to automate tasks directly, cutting down the manual time between thinking and doing,” he explains. “That’s when we’ll start to see real HyperProductivity.”
The transformation isn’t about replacing workers—it’s about evolving how they work. “AI won’t take your job,” Bloch concludes, “but someone who knows how to use AI better just might.”
As AI becomes more deeply embedded in everyday tasks, companies that fail to manage AI assistant coordination in enterprises risk losing not only productivity but also strategic direction. Those who succeed will empower their workforce—and redefine how work gets done.
