AI Adoption Roadmaps: The Missing Link in AI Success Stories

Janine Dormiendo
Oct 10
5 min read

Even as organisations rush to adopt generative AI and machine‑learning tools, many find that momentum stalls. Pilots succeed—but scale flounders. ROI is murky. And culture and governance lag behind. The missing link? A robust AI adoption roadmap grounded in adoption maturity mapping.

mapping is critical for long‑term success. It surfaces strategic gaps, and a guided workshop to co‑create a roadmap is often the turning point between ambition and outcome.

Why adoption maturity mapping is essential

From adoption to value: the gap many organisations miss

It is no longer enough for firms to experiment with AI — the real challenge is scaling it meaningfully across functions, with governance, culture, and measurable impact.

BCG: “AI at Work 2025: Momentum Builds, but Gaps Remain”. This survey (based on >10,600 workers across 11 countries) finds that only 51 % of frontline employees are regular users of AI tools — meaning adoption isn’t yet pervasive at the execution level within organisations Yet we know that personal use is much higher than that.

In IDC’s 2025 Enterprise AI Transformation study (1,213 organisations), only about 14 % are in the “AI Masters” level (i.e. fully mature), while 15 % are “Emergents” (at the earliest stage) and the rest (35 % “Pioneers” and 36 % “Leaders”) are somewhere in between. (NetApp)

IBM’s recent observations suggest that as adoption matures, organisations shift from fragmented AI experiments to integrated, strategic deployments across core business areas. (IBM TechXchange Community)

These data points emphasise that adoption alone is not enough; maturity — the degree to which an organisation’s capabilities, governance, culture, and infrastructure are aligned — is what differentiates sustainable success.

What does “maturity” in AI adoption mean?

Maturity is a multidimensional concept. Leading frameworks emphasise dimensions such as:

Strategy & Roadmap
Data readiness and governance
Technology platforms and integration
Organisational design, culture, and change management
Governance, ethics, risk and compliance
Measurement, metrics, and feedback loops
Ecosystem and external partnerships

For instance, MIT Sloan cites that firms in more advanced maturity stages outperform peers financially; early and mid-level adopters often lag in performance. MIT Sloan

MITRE’s AI Maturity Model emphasises six pillars (e.g. Strategy & Resources, Data,

Technology Enablers, Organisational, Performance) to guide practical progression.

In short: maturity means embedding AI not as a tool, but as part of how the organisation operates.

How adoption mapping becomes a strategic tool

An adoption maturity map is not just a snapshot — it is a strategic instrument. Here’s how it helps:

Clarifies current state and blind spotsTeams often overestimate readiness in some dimensions (e.g. tech) while underinvesting in others (e.g. culture or change). A structured maturity mapping exercise surfaces these discrepancies.
Aligns a shared language and aspirationAcross leaders, technical teams, operations, legal, HR—everyone begins to speak from the same dimensions. This alignment reduces confusion, silos, and misprioritisation.
Reveals constraints and dependenciesYou might want to scale a use case, but realise that poor data architecture or lack of governance will block it. The map helps you see dependencies (if we don’t level up data readiness, trying to scale will fail).
Supports prioritisation with a line of sight to valueRather than chasing every possible AI use case, the roadmap helps you sequence interventions (e.g. improve data pipelines first, invest in change‑management, then scale use cases in high‑impact areas).
Provides a mechanism for measurement and feedbackBecause the map is structured, you can track progress over time. Which dimensions advanced? Where did you stall? This enables continuous improvement.

In essence: adoption maturity mapping is the bridge from vision to execution.

The workshop: Aligning teams on priorities and actions

To make the roadmap practical and actionable, many organisations employ a facilitated workshop structured around maturity mapping. Below is a typical flow (customised per organisation):

Phase	Purpose	Outcomes
Pre‑work & assessment	Distribute a readiness survey to key stakeholders to baseline each maturity dimension	Pre‑scored dimensions and qualitative insights; shared baseline data
Framing & context setting	Introduce maturity framework, map industry benchmarks, and clarify goals	Shared understanding of maturity models; expectations calibrated
Current state mapping	In small groups or across teams, assess current maturity across dimensions	Co‑created current maturity map, with annotated strengths and gaps
Future aspiration & gap analysis	Define target maturity horizon (e.g. 12–24 months) and identify gaps	A “delta map” showing what needs to move in which dimensions
Roadmap design & prioritisation	Brainstorm initiatives, cluster into waves (quick wins, mid‑term, long term), allocate roles	Initial roadmap with a handful of priority initiatives and sequencing
Alignment & governance	Debate trade-offs, resource allocation, and accountability mechanisms	Clear ownership, governance model, and shared commitment
Measurement & next steps	Define metrics, milestones, and feedback loops	A living dashboard or scorecard and timetable for review

When done well, this exercise does more than produce a roadmap — it aligns leadership, surfaces tensions intentionally, and embeds accountability.

Some metrics often surfaced in such workshops include:

Adoption rate (what percent of employees use the AI tool weekly)
AI‑assisted work ratio (e.g. what proportion of tasks are aided by AI)
Use‑case pipeline health and time to pilot
Value realised vs target (cost savings, revenue uplift, productivity)
Dimension‑level maturity scores (e.g. data, governance, change)

As teams progress, you can re-run the mapping exercise at intervals (e.g. every 6–12 months) to reflect evolution.

In practice: Why the roadmap is often the turning point

Consider these illustrative dynamics (anonymised composite from client experience):

A business unit wants to scale an AI chatbot for customer service. They rush to deploy. But usage stagnates because front‑line agents lack trust, governance is unclear, data pipelines break, and leaders are misaligned.
With maturity mapping, the team realises the largest barrier is change management and agent training, not further algorithm tuning. In the roadmap, they sequence: design a pilot unit, invest in upskilling, define escalation flows, then scale.
Six months later: usage doubles, error rates drop, agents adopt it as a tool—not a threat.

In many cases, working with clients, once the maturity mapping is surfaced, sceptics shift. They see where resources need to go—not just in tech budgets, but in culture, governance, risk, measurement, and change.

Caveats, challenges, and best practices

Maturity is not a grade competition: The aim is not to “score 5/5,” but to chart realistic progression. Some dimensions will advance faster than others, given context.
Customisation is necessary: No two organisations are alike. The maturity map must reflect your structure, culture, regulatory constraints, and strategic priorities.
Workshop facilitation is critical: A skilled facilitator helps push the conversation past superficiality to honest tension and trade‑offs.
Hold the roadmap lightly: External conditions shift (e.g. regulation, market, tech). The roadmap must be a living instrument—not a rigid contract.
Embed governance and review: Without periodic check‑ins, even the best roadmaps drift.

Conclusion

AI adoption is not just a technical journey—it’s a transformational one. The stories most often told are about algorithms and models; the stories less told are about change, alignment, and endurance. Organisations that treat adoption as a one‑off launch, without a mapped roadmap, often find themselves back at square one.

Adoption maturity mapping provides the structure to move from pilots to purposeful scale. A workshop to align leadership and co‑create that roadmap is often the catalytic moment in any AI success story.

Ready to move beyond pilots?

If your organisation is serious about turning AI potential into practical outcomes, an adoption roadmap is your next strategic step. The AI Strategy Workshop™ is designed to help leadership teams build clarity, alignment, and momentum—based on your current maturity.

Book a 30-minute executive briefing to explore how the workshop can support your priorities: 👉 info@envisago.io | envisago.com