Automation can deliver tremendous value—but as organizations scale AI-enabled workflows, a new challenge is emerging: governance debt.

In this episode of TechEDGE, Teresa Huck examines why CIOs must manage automation as an enterprise portfolio rather than a collection of individual projects. While each automation may deliver measurable value on its own, unmanaged growth can lead to fragmented ownership, duplicate workflows, hidden dependencies, and increasing operational risk.

Learn why visibility, accountability, risk-based governance, and clear ownership are becoming essential for organizations that want to scale AI-enabled automation without sacrificing agility or return on investment.

What You'll Learn

- What governance debt is and why it grows alongside automation

- Why automation should be managed as an enterprise portfolio

- How fragmented ownership creates unnecessary complexity and risk

- The 10 questions CIOs should ask before approving an automation pipeline

- The four layers of an effective automation governance framework

- Why AI agents require clear limits on decision-making authority

- How risk-based governance enables innovation without creating bottlenecks

Why It Matters

The challenge isn't automation—it's governing automation at scale.

As AI-enabled workflows become more autonomous, organizations need an operating model that balances innovation with accountability. The companies that achieve the greatest return on automation won't necessarily deploy the most workflows—they'll be the ones that establish clear ownership, maintain visibility, and avoid accumulating governance debt over time.