Bounteous study highlights gaps and progress in enterprise AI adoption

Bounteous, a digital transformation consultancy, has released findings from its global study titled “The AI Whitespace: Addressing Challenges to Unlock Potential”, which explores how enterprises are integrating artificial intelligence (AI) and where significant obstacles remain in achieving enterprise-wide transformation.

The report draws on insights from over 300 senior decision-makers in marketing and technology roles at organisations with annual revenues exceeding USD 500 million. While AI adoption appears widespread, with 93% of companies reporting expected or better returns on investment, the study finds that governance challenges, skill gaps, and fragmented implementation continue to hinder more comprehensive outcomes.

Although AI is reportedly delivering measurable returns, many deployments remain limited in scope. The study reveals that half of all respondents have experienced higher-than-expected returns from their AI initiatives, suggesting that AI is moving beyond the experimental phase and generating clear value. However, progress remains uneven across functions and industries.

Generative AI tools are widely used across enterprises. Predictably, adoption of platforms from Google (70%) and Microsoft (69%) remains high due to existing enterprise partnerships. However, 73% of respondents reported using OpenAI tools, and 35% said they had developed proprietary AI platforms internally. A significant 95% of organisations rated AI adoption as important or very important, while 65% of executives identified it as their organisation’s top priority over the next 12 months.

The marketing function is currently realising faster benefits from AI than IT. According to the study, 59% of marketing leaders reported higher-than-expected returns, compared with 43% of IT leaders. This suggests that marketing teams find it easier to deploy and scale AI initiatives than their counterparts managing more complex IT systems.

Image Credits- Bounteous Study

A notable gap was observed between executive perceptions and the experiences of frontline teams. Executives were twice as likely as non-executives to describe their organisation as “expert” in AI maturity. This points to a potential misalignment between leadership assessments and operational realities.

Ownership of AI initiatives remains siloed. The study found that 46% of organisations place AI under the remit of the CIO or CTO, while only 3% have established cross-functional taskforces or Centres of Excellence to coordinate AI strategy and implementation. This fragmented approach is contributing to inefficiencies and missed opportunities.

Respondents cited legal and regulatory compliance, limited internal knowledge, and low trust in AI systems as the primary barriers to broader adoption. Addressing these challenges, the report notes, will require stronger governance frameworks, workforce training, and better cross-functional coordination.

In terms of strategic focus, many organisations are prioritising short-term gains. Around one-third of respondents reported focusing on embedded AI features and workforce productivity. In contrast, only 15% are currently investing in engineered AI solutions, and 22% are developing long-term, holistic AI strategies. These figures suggest that a substantial portion of AI’s potential within the enterprise remains untapped.

Martin Young, Executive Vice President of Data & AI at Bounteous, commented that AI’s full impact is yet to be realised. He stressed the need for organisations to treat AI as a long-term investment, embed it within the fabric of the business, and overcome internal silos to unlock sustainable transformation.

Sector-Level Insights: AI adoption priorities across industries

The study also analysed AI adoption patterns across seven key industry sectors, Financial Services, Technology, Marketing/Advertising, Telecommunications, Healthcare, Travel & Hospitality, and Retail/Consumer Dining, as well as among different leadership roles, including C-suite executives and IT leaders.

Below are summary findings from four of these sectors: Healthcare, Financial Services, Travel & Hospitality, and Retail/Consumer Dining.

In Travel & Hospitality, 44% of respondents reported focusing on AI features embedded within their existing software platforms. This was followed by 39% in Financial Services, 32% in Healthcare, and 30% in Retail, Consumer, and Dining.

AI is also being used to enhance team productivity. In Retail, Consumer, and Dining, 34% of leaders are leveraging AI to support workforce efficiency. This compares with 32% in Healthcare, 31% in Travel & Hospitality, and 30% in Financial Services. These results suggest that consumer-facing sectors are placing a higher emphasis on enabling employees through AI tools.

When it comes to planning for future AI capabilities, 25% of leaders in Retail, Consumer, and Dining reported having long-term AI strategies in development. This contrasts with 20% in Healthcare, 15% in Financial Services, and 14% in Travel & Hospitality, indicating that retail leaders are placing greater strategic emphasis on future AI readiness.

Finally, Financial Services (17%) and Healthcare (16%) reported the highest focus on developing custom AI solutions. In comparison, only 11% of respondents in both Travel & Hospitality and Retail, Consumer, and Dining reported investment in engineered AI tools or products.