By Bob Violino

Copyright cnbc

There are steps technology and business leaders can take to help their organizations thrive with AI.

One is to clearly define the human-AI partnership. Leaders should approach agentic AI integration as “a symbiotic relationship with existing talent,” Diasio said. “This means crafting a strategy that outlines what tasks AI will handle and what roles humans will play. [This] approach is a more effective and engaging way to leverage agentic AI, helping to alleviate employee fears and foster a more collaborative environment.”

Another good practice is to turn “tacit knowledge” into knowledge assets, Diasio said. “Jobs are performed through know-how and experience, which is information that may exist only in workers’ heads, not aggregated in historical databases,” he said. “Agentic AI needs this organizational knowledge to guide effective decision-making with a consistent methodology.”

With autonomous agents, the potential for both positive and negative outcomes is greatly improved and technology leaders need to address this.

“Recently, we’re starting to get more news of the cyber [security] implications in many agents, and that will only grow with more agents being pushed into production,” Diasio said. “Therefore, it is crucial to establish a responsible AI framework and a cyber plan optimized for AI from the outset.”

This involves setting clear policies on data privacy and security, ethical use, and oversight to determine the specific points where human review is mandatory, Diasio said. “By proactively addressing these governance questions, leaders can build a trustworthy and transparent system that aligns with company values, manages risk, and builds confidence among employees and stakeholders,” he said.

Even with the potential risks, businesses also need to democratize access to AI tools. “The barrier to AI implementation has significantly lowered; one no longer needs to be an [machine learning] engineer to create value,” Mathur said. “Forward-thinking organizations should prioritize democratizing access to agentic AI tools within a well-defined security framework.”

This empowers employees to be innovative within their daily tasks. “Over-reliance on centralized AI councils or steering committees can create bottlenecks and stifle this bottom-up innovation,” Mathur said. “True progress requires leaders to actively champion and enable this widespread adoption.”

Another good practice is to create an AI center of excellence. “The most successful enterprises are building small, elite teams of ‘AI blackbelt’ specialists who operate as a horizontal center of excellence,” Mathur said. “These experts embed directly within various business functions, not to do the work for them, but to enable and train those teams to build their own agentic workflows.”

In addition, businesses need to be smart about setting goals for AI. “Be specific with internal teams on desired outcomes, find ways to measure success,” Mathur said. “Objectives should be achievable, realistic and targeted for achieving within mutually agreed upon timelines by the team.”