AI ROI Grows, But Organizations Struggle to Embed Business Expertise

As AI adoption accelerates across industries, organizations are beginning to see tangible benefits from their investments. However, new research reveals that translating business expertise into AI-powered workflows remains a critical hurdle on the path to greater ROI.

According to Alteryx’s 2026 IT Leader Research: The State of AI Ownership, Agents, and ROI report, most organizations expect their AI budgets to increase over the next two years. Companies are investing not only in AI models but also in supporting technologies, including data platforms, automation tools, infrastructure, and governance capabilities.

Most surveyed IT leaders report moderate or significant returns from AI initiatives, but proving and scaling that value remains a challenge. Organizations are under pressure to demonstrate improvements in productivity, cost efficiency, and business outcomes.

Business context is key to getting more from AI

Respondents identified business context as one of the most important ingredients for successful AI. However, many organizations struggle to embed their operational knowledge, processes, and expertise into AI systems, which limits the relevance and accuracy of AI-generated outputs.

This study shows that IT leaders are optimistic about agentic AI, which can perform tasks and make decisions with autonomy. Most believe these technologies could deliver meaningful business value within the next few years. However, organizations should have the right controls and data foundations in place.

Data access continues to hold back AI adoption

According to this research, only some organizations have achieved full self-service access to cloud data for business customers. Limited data accessibility continues to slow AI adoption, reduce efficiency, and create bottlenecks between business and technical teams.

Many organizations have not clearly defined who owns AI initiatives or how AI systems should be governed. These uncertainties can increase risk, hinder scaling efforts, and make it more difficult to achieve reliable outcomes from AI investments.

This report highlights a few organizations that are significantly ahead in AI maturity. These leaders tend to combine strong governance, better data access, effective cooperation between IT and business teams, and a clear focus on measurable outcomes.

IT and business teams must work together on AI

Organizations should focus on building a stronger connection between business expertise and AI systems rather than simply increasing technology investments. IT and business teams need to work closely together to ensure AI tools understand organizational processes, goals, and decision-making requirements. Companies should also establish clear governance frameworks, define ownership of AI initiatives, and create safeguards that enable AI to be deployed responsibly and at scale.

Lastly, organizations must improve access to high-quality data and reduce barriers that prevent employees from using it effectively. Companies that make data more accessible, invest in automation, and embed business context into AI workflows are more likely to generate measurable returns from AI initiatives. This report also suggests that leaders should prioritize outcomes (such as productivity gains, cost savings, and business impact) and prepare for the adoption of agentic AI through stronger data foundations and governance practices.