I recently facilitated a succession-planning workshop where two realities surfaced: one senior leader hadn’t considered AI at all, and another led a team that viewed it as a threat to service delivery. Both positions undermine readiness. If your succession plan ignores Artificial Intelligence (AI), you’re planning for a world that won’t exist in five years.

McKinsey’s latest global survey finds the most significant impact comes from redesigning workflows, not from adding isolated tools to your workflow —exactly the kind of change leaders must plan their talent around adopting AI into their workflow and service delivery.

Below I share 5 practical pathways for you to consider now. 

(Read more: McKinsey—The State of AI). 

Clarify where AI fits (start with work, not tools)

Begin with the work your team does every day. List the few tasks that eat time, involve copy-and-paste, or require lots of back-and-forth. Those are your best candidates to try AI on.

♟️Make a short list: Write down 5 time-hungry tasks (e.g., drafting routine emails, summarizing meetings, creating first-draft reports).

♟️Pick 1–3 to test: Choose quick wins—small, repeatable tasks with clear owners.

♟️Define simple “win” signs:

• • Time saved: “This now takes ~10 minutes less.”
  • Fewer do-overs: “We need fewer edits/hand-offs.”
  • Faster response: “Clients get answers

♟️Run a small test (about 6–8 weeks): Keep a before/after note for each sign above.

♟️Keep what works: Save the winning prompt and a one-page “how we do it” checklist; drop what doesn’t.

Why this approach works: Organizations that redesign the way work flows see the biggest gains—it’s far more than just adding another app. 

(Read more: McKinsey—The State of AI).

Map the work. (Start where time and errors pile up) 

List the five tasks that consume the most time or create the most mistakes. Pick 1–3 to run a small AI test. Define success in simple terms:

♟️Get work done faster,

♟️Cut rework

♟️Improve client satisfaction. 

(Read more: McKinsey—The State of AI).

Set guardrails early (governance that enables delivery)

Publish simple rules of the road: approved use cases, data handling standards, human-in-the-loop checkpoints, and documentation. Anchor to recognized frameworks so your approach scales with growth. (Read more: NIST AI RMF Playbook; ISO/IEC 42001—AI Management Systems).

Pilot → measure → scale (institutionalize learning)

Pilots reduce risk and build confidence by proving value on a small scale before you invest broadly. They also create shared evidence your leadership team and frontline staff can trust. Use this simple sequence to turn lessons into a repeatable practice across teams.

♟️Run a short test (8–12 weeks). Pick 1–3 tasks.

♟️Write down today’s numbers before you start (time per task, do-overs, client satisfaction).

♟️Meet briefly every two weeks for a “show and tell” to see what’s working and what isn’t.

♟️Save what works as simple templates—your best prompts, a one-page “how we do it” checklist, and a quick quality check step.

♟️Expand carefully. If the test improves speed/quality/client feedback, roll it to the next team and measure again.

Use a simple quality loop: Plan → Do → Check → Act.

• Plan: choose the task and what “better” means.

• Do: run the small test.

• Check: compare before/after notes.

• Act: standardize what worked (template/checklist) and move it to the next team.

Just a short test, a few easy numbers, and a habit of saving what works.

Communicate the purpose (adoption follows clarity)

People adopt what they understand. Explain why the pilot exists (to reduce low-value work and improve client outcomes), how quality will be verified, and what support they’ll receive.

♟️Use a structured change approach such as ADKAR, to guide awareness, desire, knowledge, ability, and reinforcement.

(Read more: Prosci—ADKAR Model).

How Grey & Associates can help

Grey & Associates partners with leadership teams to make succession planning actionable in an AI-enabled environment:

• AI-Ready Succession Audit: Assess roles, workflows, and risk controls against best-practice frameworks.

• Capability Mapping & Upskilling Plan: Embed AI fluency into role profiles and learning paths.

• Pilot Design & Measurement: Select high-value use cases, define metrics, and run disciplined tests.

• Practical Governance: Stand up guardrails aligned with NIST AI RMF and ISO/IEC 42001. 

Ready to align your succession plan with how work will actually get done?

Schedule a consultation: https://bit.ly/grey-discovery-website

Meet Dr. Grey

Dr.Keisha Grey, founder and principal consultant of Grey & Associates, is a visionary leader and seasoned consultant passionate about driving positive change within organizations and communities. With over 15 years of experience in organizational development, leadership assessment, strategic planning, and community engagement, Dr. Grey brings expertise and a proven track record of success to every project.