by Braden Kelley and Chateau G Pato
What Questions Do Smart Boards Ask About the Next Five Years? (Short Answer)
Seven questions smart boards ask about the next five years: (1) Which landing are we buying — soft or hard? (2) What stays human-accountable as machines act? (3) Is work redesign funded with the technology bet? (4) Can the organization absorb the change portfolio we are approving? (5) How do trust and human success hold when agents and automation scale? (6) How will we know we are winning — outcomes, not theater? (7) Which capabilities will still matter when the tool stack turns over? Weak answers optimize for slides and takeout. Strong answers name ownership, dignity, capacity, and a scoreboard humans can live with.
Smart boards do not ask whether the future is coming. They ask which future the company is paying for — and who will still be able to succeed inside it.
Why Is Strategy Without a Landing Just Spend?
I have sat through five-year strategy sessions where the AI line item was confident, the competitive-parity slides were polished, and nobody could say — in one human paragraph — what kind of organization would exist if the bets worked. Efficiency takeout was clear. Accountability, redesign, and change capacity were “in the plan.”
The next five years will not be won by boards that only ask about spend and speed. Soft landings are designed. Boards either demand that design — or rubber-stamp a harder one.
| Question | Weak answer | Strong answer |
|---|---|---|
| 1. Soft or hard landing? | Compete and cut cost with AI | Named what machines absorb / humans keep |
| 2. Human accountability? | “Ethics is being stood up” | Decision rights, undo, who answers why |
| 3. Work redesign funded? | Training is in the plan | Budget and mandate beside the tech |
| 4. Change capacity? | Everything is priority | Stop/start rules; what we will not ask |
| 5. Trust at scale? | NPS/SLA still strong | Human success can stop a green review |
| 6. Winning without theater? | Adoption and maturity KPIs | Behavior, value, transfer to BAU |
| 7. Capabilities that age? | Upskill on AI tools | Judgment skills + time to practice |
1. Which Landing Are We Buying — Soft or Hard?
Why smart boards ask: Technology strategy is not neutral. It either protects human judgment and agency or densifies leftover work.
Weak answer: “We’re investing in AI to stay competitive and reduce cost.”
Strong answer: A named soft landing — what machines absorb, what humans keep, what deep work and dignity we will protect.
Demand next: One paragraph in the strategy that defines the landing in human terms — not only the vendor roadmap. For the designed split, see The AI Soft Landing; for how common pitches land both ways, see 10 Futures Being Pitched in 2026.
2. What Stays Human-Accountable as Machines Act?
Why smart boards ask: Autonomy without ownership is liability with a demo.
Weak answer: “Governance and ethics are being stood up.”
Strong answer: Named decision rights, undo, escalation, and who can be asked why when an agent acts — for customers and for internal decisions.
Demand next: An accountability map for the highest-stakes agentic or automated paths — not a principles poster. For what leaders must own by scenario, see 5 Scenarios for Agentic Organizations.
3. Is Work Redesign Funded With the Technology Bet?
Why smart boards ask: Tools without redesigned jobs produce efficient misery and burned-out “exception handlers.”
Weak answer: “Change management and training are in the plan.”
Strong answer: Budget and mandate for job redesign, incentives, retirement of the old path, and manager development — tied to the same investment case as the tech.
Demand next: Line items and owners for redesign — not a training completion KPI as proxy.
4. Can the Organization Absorb the Change Portfolio We Are Approving?
Why smart boards ask: Strategy that stacks initiatives until humans break is not ambition — it is extraction.
Weak answer: “Everything is priority; we’ll sequence in PMO.”
Strong answer: Visible portfolio load, stop/start rules, and what will not be asked of the frontline this horizon.
Demand next: A capacity view beside the initiative list — what stops if this starts. If the organization is already optimizing for the wrong future of work, see 8 Signals You’re Preparing for the Wrong Future of Work.
5. How Do Trust and Human Success Hold When Agents and Automation Scale?
Why smart boards ask: Green operational metrics can hide red journeys. Containment is not care.
Weak answer: “CSAT/NPS and SLAs remain strong.”
Strong answer: Experience-level measures, recovery power, and customer/employee moments that matter — with owners who can change the system.
Demand next: One critical journey where human success can stop a “green” review. For the moments that outrank a scoreboard, see 8 Moments That Matter More Than Your NPS Dashboard.
6. How Will We Know We Are Winning — Outcomes, Not Theater?
Why smart boards ask: Five-year decks love activity — pilots, platforms, “AI maturity.” Boards need landings.
Weak answer: “We’ll track adoption, usage, and innovation KPIs.”
Strong answer: Adopted behavior, retired workarounds, value captured, kill rate with honor, transfer to BAU — outcomes that decide funding and promotion.
Demand next: A short scoreboard that demotes vanity metrics; theater cannot close the quarter. For the catalog, see 12 Metrics That Actually Measure Innovation Value.
7. Which Capabilities Will Still Matter When the Tool Stack Turns Over?
Why smart boards ask: Buying the next model is not building an organization that ages well.
Weak answer: “We’re upskilling everyone on AI tools.”
Strong answer: Investment in problem framing, sense-making, judgment, empathy with stakes, facilitation, repair, and meta-learning — and contiguous time to practice them.
Demand next: Hiring, promotion, and calendar design that reward those capabilities — not only prompt fluency. For the list, see 9 Skills That Age Well When Everything Automates.
How Do Smart Boards Run a Five-Year Readiness Check?
Before the next strategy offsite, run five go/no-go questions:
- Can we describe our landing in one human paragraph?
- Who is accountable when machines act?
- Where is redesign funded beside the tech?
- What will we stop so capacity is real?
- Which outcome metrics — not activity — will tell us we are winning in year three and year five?
Smart boards don’t buy the pitch. They buy the landing — and the humans who must live it.
Frequently Asked Questions
What questions should boards ask about AI and the future?
Boards should ask which soft or hard landing the AI strategy buys, what stays human-accountable as machines act, whether work redesign is funded with the tech, whether the organization can absorb the change portfolio, how trust and human success hold at scale, how winning will be measured without theater, and which capabilities will still matter when tools turn over.
What is a soft landing for boards?
A soft landing for boards is a five-year strategy where machines absorb fragmentation and low-judgment transaction while humans keep judgment, accountability, dignity, and contiguous time for meaningful work — with redesign, change capacity, and outcome metrics funded beside the technology bet. A hard landing densifies leftovers and calls it progress.
How should boards govern AI over five years?
Boards should govern AI over five years by demanding an accountability map for high-stakes automated action, funding work redesign with the investment case, insisting on portfolio stop/start honesty, requiring human-success measures that can stop green operational reviews, demoting vanity AI maturity metrics, and investing in capabilities that age past the next model cycle.
What should boards ask about change capacity?
Boards should ask whether the organization can absorb the change portfolio being approved — with a visible load view, stop/start rules, and clarity on what will not be asked of the frontline. Stacking every initiative as “priority” without capacity is extraction dressed as ambition.
How do boards measure AI success beyond pilots?
Boards measure AI success beyond pilots with outcomes that decide funding and promotion: adopted behavior, retired workarounds, value captured, honorable kill rate, and transfer to BAU — not only usage, adoption percentages, or “AI maturity” theater.
Image credits: Gemini
Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini and Cursor to clean up the article, add images and create infographics.
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.