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Who owns your business processes?

Strong processes don't happen by accident. They require clear ownership, accountability, and continuous improvement.

Without a clear owner, processes can become inconsistent, outdated, and difficult to optimize.

We're curious:
Who typically owns business processes in your organization?

✅ A dedicated process owner
✅ IT or technology teams
✅ Business departments
✅ It depends on the process

Share your experience in the comments.

Technical debt gets a lot of attention.

But process debt can quietly undermine digital transformation, operational resilience, and technology investments.

The first step is understanding where your processes stand today.

Your Processes Are Assets. Treat Them Like It.

Many organizations manage their technology, data, and financial assets carefully.

But what about their processes?
Processes determine how work gets done, how decisions are made, and how value is delivered.

Without ownership, governance, and continuous improvement, processes become outdated, and operational risk grows.

Process governance ensures your processes remain aligned with business goals, regulatory expectations, and changing organizational needs.

Your processes aren't just documentation.
They're business assets.

Technical debt is a familiar concept. But what about Process Debt?

As organizations accelerate AI adoption, digital transformation, and operational resilience initiatives, poorly governed and outdated processes become a hidden source of risk.

In this video, David Mainville explains why governance doesn't live in frameworks, it lives in the processes people execute every day.

https://hubs.li/Q04qG65K0

AI Governance Tip #5: Trust Requires Explainability

AI doesn't have to be perfect.
But it does have to be explainable.
If your organization cannot explain:

- Why a recommendation was made
- How a decision was generated
- What factors influenced the output

Then trust becomes difficult to maintain.
Regulators, customers, executives, and employees increasingly expect transparency in AI-enabled decisions.

A useful governance question:
"Can a non-technical executive understand why this AI reached its conclusion?" If not, more work may be needed.

When organizations think about operational resilience, the conversation often starts with cybersecurity, disaster recovery, or compliance. But resilience begins earlier, with the processes that support daily operations.

Our latest blog explores why strong ITSM processes are the foundation of resilient organizations ⬇️

Operational Resilience Starts With ITSM Processes Discover how operational resilience starts with ITSM processes, helping organizations strengthen service management and safeguard against threats.

When organizations think about operational resilience, the conversation often starts with disaster recovery, cybersecurity, or compliance.

Those are all important, but they're not the foundation.
The strongest resilience strategies begin much earlier, with well-designed, documented, and governed business processes.
If you don't understand how work gets done today, it's difficult to:

✔ Identify critical services
✔ Understand operational dependencies
✔ Assess risk effectively
✔ Respond confidently when disruptions occur

Operational resilience isn't built during a crisis.

It's built every day through better processes.

Learn more in our latest webinar: Operational Resilience in Practice: Where to Start and How to Scale. https://hubs.li/Q04q220d0

AI Governance Tip #4: Ownership Is the Most Overlooked AI Control

When an AI incident occurs, who is accountable?

The answer shouldn't be:
❌ IT
❌ Security
❌ Compliance
❌ Everyone
It should be a named individual.

One of the biggest causes of unmanaged AI risk is unclear ownership and accountability. Governance frameworks fail when responsibilities are assumed rather than assigned.

Every AI capability should have:
- A business owner
- A technical owner
- A risk owner

No owner = No governance.

Question: Who owns AI risk in your organization today?

AI Governance Tip #3: Operational Resilience Means Planning for AI Failure

Many organizations are designing processes that depend on AI. Few are asking: "What happens when the AI isn't available?"

If a critical business process depends on AI:

- Is there a manual workaround?
- Is there an alternate process?
- Has it been tested?

Operational resilience isn't about assuming AI works.
It's about ensuring the business can operate when it doesn't.

The best AI governance programs don't prepare for success. They prepare for failure.

Question: Could your most important AI-enabled process run manually tomorrow?

AI Governance Tip: If you Can't Inventory AI, You Can't Govern It ⬇︎

Most organizations are asking:
"How do we govern AI?"
But they're skipping the first question:
Do we even know where AI is being used?

You can't assess risks, assign accountability, or implement controls if AI tools, models, and use cases aren't inventoried.

A surprising number of organizations have:
- Approved AI tools
- Unapproved AI tools
- Shadow AI usage
- No clear ownership

Before creating an AI Governance Committee, start with an AI Inventory.

✅ Identify every AI system in use
✅ Assign a business owner
✅ Classify risk and criticality
✅ Review regularly

Good governance starts with visibility.
Question: Has your organization formally inventoried AI use cases yet?