C-Suite AI Leadership · 8 Questions · 4 Minutes

Executive AI Maturity Assessment

Benchmark your AI leadership against 200+ global enterprises. Calibrated by our partners who have deployed AI across 40+ countries — this is not a vendor sales tool. This is the same framework we use in executive briefings for Fortune 500 boards.

Designed for CEO, CFO, COO, CTO, CHRO 5 maturity levels with executive benchmarks Strategic next-step recommendations

Question 1 of 8 Executive Assessment

How central is AI to your current corporate strategy?

Strategic positioning of AI — as a cost tool, efficiency play, or transformative capability — determines programme scale, investment, and competitive ambition.

Not in our strategy

AI has not yet appeared in our corporate strategy documents or board agenda.

Mentioned as a future priority

AI features in strategy as a medium-term initiative but has no current programme or owner.

Active AI programme — one of several priorities

AI programme exists and is funded but competes with other transformation programmes for attention and resource.

AI is a top-3 strategic priority with board mandate

AI has explicit board mandate; features in investor communications; dedicated C-suite accountability.

AI defines our competitive model

AI is the primary source of competitive differentiation in our operating and business model.

What percentage of your technology budget is allocated to AI and advanced analytics?

Benchmark: enterprises achieving material AI ROI allocate 15–30% of technology spend to AI. Top-quartile performers allocate 30%+.

Less than 2% — no dedicated AI budget

AI is funded from discretionary IT lines rather than a dedicated programme budget.

2–8% — exploratory budget

Sufficient for pilots and PoCs; not yet at scale deployment funding levels.

9–15% — funded programme

Material AI investment; able to deploy in multiple use cases and business units.

16–30% — enterprise AI transformation budget

AI is a strategic investment priority; multi-year committed funding with board visibility.

30%+ — AI-led investment strategy

AI dominates technology investment; is a material line in the capital allocation plan.

How do you measure ROI from AI investments?

ROI measurement maturity is the strongest predictor of sustained AI programme investment. Organisations that can't measure AI ROI lose budget in the next cycle.

We don't measure AI ROI

No framework exists; AI investments are approved on strategic intent rather than financial case.

Qualitative benefits only — no financial metrics

We track sentiment, adoption rates, and qualitative feedback — not financial outcomes.

Business case ROI for each initiative

ROI is defined at initiative level at approval; post-deployment measurement is inconsistent.

Formal AI portfolio ROI tracked quarterly

AI programme ROI is tracked in a portfolio view and reported to board/ExCo quarterly.

Real-time AI value dashboard — financial + operational KPIs

Live AI value measurement across all programmes; feeds capital allocation decisions in real time.

What AI governance and ethics framework does your organisation have?

As the EU AI Act, MAS FEAT, and sector-specific AI regulations tighten, governance is moving from a nice-to-have to a prerequisite for AI deployment in regulated industries.

No AI governance framework

AI decisions are made on a case-by-case basis with no formal governance structure.

Basic AI ethics policy drafted

A policy document exists but is not embedded in procurement, deployment, or review processes.

AI governance committee and risk review process

Formal AI review process for new deployments; governance committee meets regularly.

Board-level AI risk oversight + regulatory submissions

AI risk is on the board agenda; regulatory submissions made where required; third-party audits conducted.

AI governance is a competitive advantage

Rigorous AI governance creates customer trust and regulatory goodwill — actively used in market positioning.

How engaged is your board on AI as a strategic issue?

Board AI literacy is a leading indicator of AI programme durability. Boards that don't understand AI struggle to allocate capital to it consistently across economic cycles.

AI has not been discussed at board level

AI is not on the board agenda; directors have not been briefed on AI strategy or risk.

AI mentioned in management updates only

AI is referenced in management presentations but not discussed as a specific strategic or risk item.

Annual board briefing on AI strategy

Board receives a regular AI strategy update; questions AI progress as part of strategy review.

Board AI committee or designated AI-literate director

Board has formal AI oversight structure; at least one director with deep AI expertise.

Board drives AI strategy — investor narrative is AI-led

Board is the primary driver of AI ambition; AI is central to capital markets and investor narrative.

How systematically do you track competitors' AI deployment and capability?

Competitive AI intelligence determines whether your programme is calibrated to win — or simply to catch up with where competitors were 18 months ago.

No systematic tracking

We read industry news but have no structured competitor AI intelligence process.

Ad-hoc monitoring — press releases and conference talks

We monitor competitor announcements reactively; no structured intelligence function.

Regular competitor AI benchmarking

Quarterly or semi-annual competitor AI capability review; feeds strategy process.

Dedicated competitive AI intelligence capability

Internal or external CI function tracks competitor AI developments continuously; informs roadmap.

We set the AI benchmark — competitors track us

Our AI capabilities are publicly recognised as industry-leading; we are the benchmark others reference.

What is your AI talent strategy?

AI talent is the single most constrained resource in enterprise AI deployment. Your strategy for accessing it determines your programme velocity.

No AI talent strategy

We have not defined an approach to acquiring AI skills — build, buy, or partner.

Hiring data scientists into existing teams

Hiring individuals into existing structure; no dedicated AI organisational design.

AI Centre of Excellence being built

Establishing a centralised AI CoE; actively recruiting AI leadership and engineering capability.

AI CoE + GCC/offshore AI talent + partner ecosystem

Hybrid model combining internal CoE with offshore AI talent and specialist implementation partners.

AI-native org design — AI embedded in every function

AI capability is embedded in every business function; AI skills are a standard hiring criterion.

Does your M&A and investment thesis incorporate AI as a value creation lever?

The fastest-growing enterprises are deploying AI immediately post-acquisition to accelerate integration ROI. AI M&A thesis signals the highest level of executive AI maturity.

AI not considered in M&A

M&A due diligence does not include AI capability assessment or AI synergy modelling.

AI assets are noted but not a deal driver

AI capability noted in due diligence but does not influence valuation or deal rationale.

AI synergies modelled in some deals

AI integration synergies are modelled as part of the business case for selected acquisitions.

AI integration plan included in all deal value creation plans

Post-merger AI deployment is a standard component of every integration plan and synergy model.

AI capability acquisition is a primary deal thesis

We actively acquire companies to obtain AI talent, data, or technology — AI drives the deal thesis.

out of 40 points · percentile

of enterprises at your level

typical time to next level

avg 3-yr ROI at next level

Executive Priorities to Advance Your Maturity