FreeMalta Intelligence Report · June 2026
The AI Adoption Gap: Why Companies Are Buying AI But Not Using It
88% of organisations now use AI in at least one business function. Only 6% are capturing meaningful enterprise-wide value. Deloitte, KPMG, McKinsey and Anthropic all see the same gap — and it has a name.
Sources
Deloitte 2026
KPMG 2025/26
McKinsey 2025/26
Microsoft 2026
Anthropic 2026
WEF 2025
88%
of organisations use AI in at least one business function
McKinsey State of AI 2025
6%
are capturing meaningful enterprise-wide AI value
Multiple sources 2026
34%
are truly reimagining their business around AI
Deloitte State of AI 2026
74%
want revenue growth from AI — only 20% are achieving it
Deloitte 2026
$124M
Average planned AI investment per organisation in next 12 months
KPMG Q4 2025
92%
of tech leaders cite skills gap as top barrier to AI agent ROI
KPMG Q1 2026
23%
of organisations report AI is exceeding expectations (KPMG Finance)
KPMG Global AI Finance 2026
74%
expect to use agentic AI to at least moderate extent within 2 years
Deloitte 2026
Section 01
The Adoption Illusion: Everyone Has AI, Almost Nobody Is Transforming
The numbers look impressive. McKinsey finds 88% of organisations use AI in at least one business function. Deloitte's 2026 State of AI in the Enterprise — based on 3,235 senior leaders across 24 countries — finds worker access to AI rose 50% in 2025 alone. KPMG reports 93% of business leaders believe their AI investments have enhanced competitive position.
And yet: only 6% are capturing meaningful enterprise-wide value. Only 34% are truly reimagining how their business operates. Revenue growth from AI remains an aspiration for 74% of organisations — only 20% are actually delivering it. There is a profound gap between AI adoption and AI transformation. Every major research firm in 2026 is pointing at the same problem from different angles.
Deloitte names it directly: organisations are standing at the "untapped edge" of AI's potential. KPMG calls it the difference between leaders who are "professionalising" their AI deployments and those who stall after early pilots. McKinsey finds that organisations which fully redesign workflows around AI report EBIT impact above 5% — while those that simply layer AI onto existing processes capture a fraction of that value.
"AI adoption is broadening faster than enterprise AI integration. Many organisations now have approved tools, live use cases, and senior-level support. Fewer have made the organisational changes required to turn those ingredients into consistent business value."
Deloitte AI Institute, State of AI in the Enterprise 2026
Section 02
What Deloitte, KPMG, McKinsey & EY Each Found
Deloitte — 3,235 leaders, 24 countries
66%
Report productivity gains. But only 20% report actual revenue growth. Worker enthusiasm is real: 55% open to exploring AI, only 4% actively avoiding it. The constraint is workflow design and management expectations, not employee resistance.
KPMG — Q1 2026 Pulse Survey
92%
Of tech leaders cite skills gap as the top barrier to AI agent ROI. 67% of leaders will maintain AI spending even in a recession. Banking leaders will pay 11–15% more for strong AI skills — an 18% increase from Q4 2025.
McKinsey — State of AI 2025
2.8x
AI high performers are 2.8x more likely to have fundamentally redesigned workflows (55% vs 20%). These same organisations report EBIT impact above 5%. Senior leadership ownership of AI is 3x more likely among high performers.
KPMG — Global AI in Finance 2026
32pts
Organisations deploying agentic AI in finance outperform by 32 percentage points on average. Decision-making quality (70%) and speed (71%) lead gains. The leaders direct AI at judgment-heavy work, not just transactional tasks.
KPMG — Trust & AI Global Study 2025
66%
Of people use AI regularly. But 56% admit making mistakes due to AI output. Only 46% globally trust AI systems. 66% rely on AI output without evaluating accuracy — the adoption-without-judgment problem in raw numbers.
Microsoft — Work Trend Index 2026
16%
Only 16% of organisations have fully redesigned operations for AI. Only 13% of workers feel rewarded for AI experimentation. The system incentivises old behaviour while expecting new results — what Microsoft calls the Transformation Paradox.
Section 03
The Three Gaps That Explain Everything
Across all the research, three gaps consistently explain why AI adoption is not translating into AI transformation:
Gap 1: The Access-Usage Gap
Deloitte finds that among workers who have AI access, fewer than 60% use it in their daily workflow — and that number has changed little year-on-year. Deployment and adoption are not the same thing. Companies have handled policy, procurement and tooling. They have not made AI a normal part of how work is performed. The constraint is not access — it is workflow integration, management design and trust.
Gap 2: The Adoption-Redesign Gap
McKinsey's data is clear: AI high performers redesign workflows. 55% of them have done fundamental redesign vs 20% of average performers. That 35-percentage-point gap in workflow redesign produces the 2.8x performance difference. Most companies buy AI tools and layer them on top of existing processes. They get marginal efficiency gains instead of structural advantage.
Gap 3: The Skills-Governance Gap
KPMG's Q1 2026 data: 92% of tech leaders cite skills gaps as the top barrier to AI agent ROI. But the skills gap is not just technical — it is also governance. McKinsey's 2026 AI Trust Survey found the average RAI (Responsible AI) maturity score is 2.3 out of 4. Only one-third of organisations have governance maturity above 3. Companies are deploying AI faster than they can govern it.
"The firms that will benefit most from AI are unlikely to be those that simply accumulate the largest number of tools or pilots. They will be the ones that build operating models capable of turning local gains into institutional advantage."
Dr. Karim Lakhani, Harvard Business School
Section 04
The Agentic AI Inflection: Where Things Get Real
Every major research firm identifies the same inflection point arriving in 2026–2027: the shift from generative AI (which produces content for humans to evaluate) to agentic AI (which reasons, plans and executes multi-step tasks autonomously). This is not an incremental upgrade. It changes the governance problem entirely.
Deloitte finds 23% of organisations already using agentic AI to a moderate extent. Within two years, 74% expect to be doing so. KPMG's pulse data shows AI agent deployment quadrupled between Q1 and Q3 2025 — from 11% to 42% — before stabilising as companies "professionalised" their deployments. Microsoft's enterprise telemetry shows AI agents grew 15x year-on-year.
The governance stakes are higher with agents. When AI produces content, a human reviews it before it goes anywhere. When AI agents execute workflows — send communications, interact with APIs, route decisions — errors have downstream operational consequences before anyone can review them. The McKinsey AI Trust Maturity Survey found that nearly two-thirds of organisations cite security and risk concerns as the top barrier to scaling agentic AI.
| AI Type |
What it does |
Current adoption |
2-year projection |
Risk level |
| Generative AI (tools) |
Produces content for human review |
88% — at least one function |
Universal |
Low-Medium |
| Agentic AI (pilots) |
Executes limited multi-step tasks |
23% moderate use |
74% within 2 years |
Medium-High |
| Multi-agent systems |
Orchestrates multiple AI agents autonomously |
16% — Frontier orgs only |
Growing fast |
High — requires governance |
🇲🇹 Malta Angle
Malta's iGaming sector is one of the most regulated environments in Europe for AI-adjacent activities — player protection, AML, responsible gaming. This creates both a constraint and an opportunity. The constraint: deploying agentic AI without robust governance frameworks would create serious regulatory exposure. The opportunity: Malta companies that build AI governance infrastructure now will have a competitive advantage when EU AI Act requirements crystallise in 2026–2027. Malta's MFSA and MGA are watching this space closely.
Section 05
What AI Leaders Do Differently
Across Deloitte, KPMG and McKinsey's research, a consistent profile of AI-leading organisations emerges. They are not necessarily the largest or best-resourced. They share specific practices:
Senior leadership owns AI, not just IT
McKinsey finds AI high performers are 3x more likely to have senior leaders who actively drive AI adoption and role-model AI use. KPMG echoes this: organisations where senior leadership shapes AI governance achieve significantly greater business value. AI transformation is a leadership challenge dressed as a technology challenge.
They redesign workflows, not just adopt tools
The single biggest predictor of AI value — across every major study — is workflow redesign. Deloitte finds only 34% of organisations are genuinely reimagining their business. McKinsey finds workflow redesign is 2.8x more common among high performers. The others are running new tools on old processes.
They invest in governance before they need it
KPMG's Finance AI report finds organisations that invest in RAI (Responsible AI) initiatives report significantly higher maturity and are far more likely to realise EBIT impact above 5%. Governance is not a brake on AI — it is what allows AI to scale safely. The organisations that treat governance as a cost to avoid are the ones that will face regulatory and reputational consequences.
They build internal AI capability, not just buy tools
KPMG's banking data shows 54% of banking leaders will pay 11–15% more for strong AI skills. Deloitte finds the AI skills gap is the biggest barrier to integration. The organisations pulling ahead are combining structured AI training programmes with clear career pathways — building the Frontier Professional cohort that generates disproportionate value from the same tools everyone else has.
Section 06
The Malta AI Adoption Picture in 2026
Malta does not have a dedicated AI adoption survey. But the global data — combined with FreeMalta's salary benchmark across 806 roles and 12 sectors — paints a picture of where Malta sits and where the gaps are.
🎮
iGaming: High tool adoption, low workflow redesign
Malta's iGaming companies are among the earliest adopters of AI tools — particularly in customer service, content moderation and fraud detection. But the pattern mirrors the global picture: tools layered on existing processes, not processes redesigned around AI. The companies generating structural advantage are those that have rebuilt their player lifecycle management, compliance monitoring and content operations workflows from scratch with AI at the centre.
💼
Financial services: Governance pressure creates opportunity
KPMG's Global AI in Finance 2026 is directly relevant to Malta's financial services sector. Organisations deploying agentic AI for finance outperform by 32 percentage points. Malta's MiFID, DORA and incoming EU AI Act requirements create a governance framework that, if embraced rather than avoided, positions Malta financial services companies ahead of less-regulated competitors.
🏢
SMEs: The Fondi.eu opportunity
The EU's Digitalise Your SME programme (Fondi.eu Call 2, opening July 2026, max €235,400) is specifically designed to fund exactly the kind of AI workflow redesign that the research shows separates leaders from laggards. Malta SMEs that apply with a genuine workflow redesign plan — not just "we'll buy AI tools" — are well positioned to capture this funding and the competitive advantage it enables.
🇲🇹 FreeMalta Assessment
Malta's AI adoption gap mirrors the global pattern, with one important difference: Malta's small size means the window for building competitive advantage is narrower. When a leading iGaming company redesigns its operations around AI, competitors notice within months — not years. The organisations that close the adoption-transformation gap in 2026 will define Malta's competitive landscape for the rest of the decade. The data is unambiguous about what that requires: leadership ownership, workflow redesign, governance investment and internal capability building. Tools are not the constraint.
Next: The Future of Work in Malta
Remote, hybrid, nomad. How AI is reshaping where work happens, what it pays, and who can do it from Malta.
Primary Sources
Deloitte AI Institute — State of AI in the Enterprise 2026 (3,235 leaders, 24 countries) · KPMG — Q4 2025 & Q1 2026 AI Quarterly Pulse Survey · KPMG — Global AI in Finance Report 2026 · KPMG — Trust, Attitudes and Use of AI: A Global Study 2025 · McKinsey — The State of AI in 2025 · McKinsey — State of AI Trust in 2026: Shifting to the Agentic Era · Microsoft — Work Trend Index Annual Report 2026 · WEF & PwC — Artificial Intelligence and the Future of Entry-Level Work 2026 · FreeMalta Salary Benchmark 2026
FreeMalta synthesises publicly available research and adds Malta-specific context. This report does not constitute professional advice.
