Learn how to transform your organization with talent intelligence platforms embedded with agentic AI to close skills gaps, cut costs, and build an agile workforce ready for change.

The AI opportunity

The race for reinvention is on.

According to PwC’s 28th “Annual Global CEO Survey,” 40% of CEOs believe that their companies won’t be viable in 10 years if they continue on their current paths. CEOs are under enormous pressure — and shrinking timelines — to turn AI’s potential into ROI, but when 70% of transformations fail, the margin for error is slim.

Today’s chief operating officers are under tremendous pressure alongside their CEOs to invest in the right AI solutions, a daunting task with so many potential use cases and types of AI. In this brief, we explore how talent intelligence platforms integrated with agentic AI can help you build more agile workforces, reduce costs, improve efficiency, and secure a competitive advantage for tomorrow.

From generative to agentic AI

Generative AI has captured the attention of nearly every business, with McKinsey estimating that gen AI could contribute up to $4.4 trillion to global GDP by 2030. According to a new study from IDC and Microsoft, organizations investing in AI see an average of $3.7 for every dollar invested, with the top 5% of leaders in AI adoption seeing even higher returns around $10 on the dollar.

In the span of months, gen AI has transformed how we work: how we source information, communicate, code, and so much more. Now, the next leap for enterprises is here — a shift from reactive, prompted tools to independent, intelligent agents that boost productivity, reduce costs, and drive competitive advantage.

The future of gen AI is agentic AI.

With the rise of AI agents — digital workers that can “reason, plan, and act” — organizations can scale workforces as needed, and adoption is already well underway. According to Microsoft research, 81% of leaders expect AI agents to be deeply integrated into their company’s AI strategy in the next year and a half. Already, a KPMG Pulse Survey states that over half of organizations “are exploring the use of AI agents, and 65% are piloting AI agents.”

82% of leaders say they’re confident that they’ll use digital labor to expand workforce capacity in the next 12–18 months.

But with high-speed, high-stakes transformations, there’s always risk.

Many AI projects fail because organizations lack the right skills. Another reason they fail, according to Deloitte, is unrealistic business use cases. The result?

Many leaders sink considerable time and capital into buying and implementing new technologies, only to change direction later or realize they have invested in redundant technologies.

For COOs to make the most of their AI investments and build workforces ready for anything, they must invest strategically.

The cost of getting agentic AI wrong

Before investing in agentic AI, it’s critical to vet vendors and ask questions to ensure you’re purchasing a true agent. Failure to differentiate between true agentic AI and false agents could lead to:

• Systems that require constant oversight and reconfiguration.
• Escalating costs from inefficiencies, redundant work, and continuous patching.
• Losing trust from systems that overpromise and underdeliver.
• Security and compliance gaps from mishandled sensitive data.
• Falling behind as competitors deploy adaptive, self-improving systems.