Alteryx, a company in the AI-ready data and analytics space, has released findings on the current state of AI adoption within enterprises. Despite significant investments in AI and automation technologies, organisations face trust and data-related challenges that limit broader implementation.
The study highlights a gap between AI ambitions and tangible outcomes. Although many companies are investing heavily in AI, real-world applications often do not move beyond the pilot stage. Currently, fewer than 25% of AI pilot projects are successfully integrated into operational frameworks.
Key Insights:
- Trust Challenges: Trust remains limited, particularly for strategic applications. Nearly half of surveyed leaders believe AI is effective for automating routine tasks, but only 28% are comfortable using it to support decision-making, and 27% trust AI for forecasting or planning.
- Importance of Data Quality: Approximately 49% of executives cite high-quality, accessible data as essential for AI to reach its full potential. Data quality issues continue to impede autonomous AI performance.
- Decentralising AI Workflows: Responsibility for AI workflows is shifting from central teams to individual business units, with an 11% increase in such decentralisation expected over the next three years.
- Increasing AI Investment: AI adoption is growing across technology infrastructures. 48% of leaders plan to increase spending on AI tools, and AI platforms are projected to grow from 33% of data stacks in 2024 to 51% by 2026.
These findings indicate that foundational issues are hindering AI initiatives. Trust declines when AI is applied without the necessary business context, often layered directly on raw data, which can lead to inconsistent outputs and reduce confidence in AI for critical business processes.
To improve AI reliability at scale, Alteryx finds that organisations should focus on data governance. This includes governed data, clearly defined metrics, and adaptable workflows that combine the capabilities of generative AI with predictable rules. Currently, 28% of leaders plan to prioritise data governance improvements to support consistent AI use.
The research also notes that AI adoption is accelerating. Compared to a year ago, two-thirds of business and IT leaders report using AI more frequently.
Responsibility for AI workflows is expected to increase from 22% to 33% within specific business lines by 2028. Organisations are continuing to invest in data quality and in integrating AI across business operations.
