AI Value Gap Assessment

What prevents AI from delivering measurable business value?

Created by a leading AI

Not a classic maturity test. This assessment reveals the gap between business pressure, knowledge capital, and execution capability. Duration: about 10 minutes.

Start assessment View methodology

4 analysis blocks

Business pressure, knowledge friction, AI enablement, execution

4 output scores

Value opportunity, accessibility, risk, execution

Benchmarks

Classification vs. industry average (anonymized)

For decision makers

Executive summary, roadmap, and PDF report

Methodology

Why this assessment?

Most AI assessments ask about tools and strategy. Organizations more often fail due to knowledge friction, silos, and weak execution. We measure the gap between pressure and impact.

How the AI Value Gap Assessment works

Developed by Kaufman AIS for mid-sized companies, this assessment connects business pressure, corporate knowledge, and AI execution in one model and shows where the largest gap between pressure and measurable impact lies.

Not a classic AI maturity test

Maturity models often ask: “Do you have an AI strategy? Do you use ChatGPT?” That says little about business impact. Instead, we measure whether knowledge is usable, whether key-person risks exist, and whether your organization can actually scale identified opportunities.

Four analysis blocks · 26 questions

Each block represents a lever along the AI value chain, from external pressure to day-to-day execution.

Block 1

Business Pressure

Where does your organization feel the greatest pressure (productivity, cost, growth, talent)? High pressure with low execution capability is a clear value gap signal.

Block 2

Knowledge Friction

How easily can company knowledge be found and used? Silos, media breaks, and key-person dependency increase knowledge risk and slow every AI initiative.

Block 3

AI Enablement

How well are data, governance, and systems prepared so AI builds on reliable knowledge, not just public models?

Block 4

Execution Readiness

Is there ownership, sponsorship, and the ability to move from pilots to measurable scale? Without this foundation, AI stays an experiment.

Four output scores

From your answers we calculate four metrics (0–100). They show not only an overall picture, but exactly where the bottleneck sits.

AI value opportunity
Untapped potential between business pressure and knowledge access. This is your biggest leverage point.
Knowledge accessibility
How easily teams can access relevant knowledge when making decisions or using AI.
Knowledge risk
Dependency on individuals, documentation gaps, and turnover risk. The higher the score, the more critical.
AI execution
Whether structures, skills, and leadership exist to bring AI initiatives into operations.

Organization profiles

Based on your scores, we assign one of four profiles. Each describes typical mid-market patterns, with clear priorities instead of generic advice.

Hidden Knowledge CompanyPilot Trap CompanyAI Ready CompanyKnowledge Risk Company

Flow in ~10 minutes

1
Company profile
Country, industry, and size for benchmark classification and contextual analysis.
2
26 structured questions
Likert scale (1–5) across four blocks. Optional: business pressure multi-select and anonymous benchmark consent.
3
Instant results
Scores, value gap, organization profile, and first recommendations, directly in the browser.
4
Full report
After unlock: executive summary, benchmark comparison, excellence roadmap, and PDF download.