Artificial intelligence has quickly become one of the biggest strategic priorities for associations. From marketing and member communications to data analysis and operational efficiency, AI is already reshaping how organisations work. But as enthusiasm grows, new research suggests that many organisations are focusing on the technology before they have built the foundations needed to use it effectively.
The EDM Association’s 2026 Global Data Management Benchmark Report, based on responses from more than 435 organisations across over 50 countries, found that while AI investment is accelerating, organisational readiness is lagging behind. Only 31% of organisations surveyed demonstrated advanced data strategy capability, despite many already investing heavily in AI initiatives. Although 77% reported having analytics programmes in place, just 19% had achieved mature adoption, highlighting a significant gap between implementing technology and embedding it effectively across the organisation.
The report argues that the problem is not AI itself, but the absence of strong data governance, clear business objectives, workforce capability, and organisational alignment. As EDM Association President John Bottega observed, organisations are often “putting technology ahead of trusted data and governance,” making it difficult for AI initiatives to deliver meaningful business outcomes.
Association leaders are encountering many of the same challenges.
Drawing on research conducted by the Center for International Private Enterprise (CIPE), association leaders expressed strong optimism about AI’s potential. The survey found that half of associations are already using AI tools, with marketing, communications, and data analysis among the most common applications. Operational efficiency was consistently viewed as AI’s greatest immediate benefit, particularly for organisations facing limited resources and staffing.
However, the research also revealed an important disconnect. While nearly all association leaders believe AI will play an important role over the next three to five years, a lack of staff expertise was identified as the biggest barrier to adoption. Most associations also acknowledged they have yet to establish formal AI policies or governance frameworks to manage emerging risks.
Rather than treating AI as a standalone technology initiative, some associations are taking a broader organisational approach. The Association to Advance Collegiate Schools of Business (AACSB), for example, has embedded AI within its strategic plan rather than limiting it to the IT department. Its organisation-wide framework includes leadership commitment, departmental assessments, workforce development, member experience, and continuous learning, recognising that successful AI adoption depends as much on people, governance, and processes as it does on technology.
The experience of organisations like AACSB reinforces a broader lesson emerging across both reports. AI readiness is not measured by the number of tools an organisation deploys. It is reflected in the quality of its data, the clarity of its governance, the capabilities of its workforce, and the ability of leadership to align technology with organisational objectives.
For association executives, the challenge is no longer deciding whether AI should become part of the organisation. That decision has largely been made. The more important question is whether the organisation has built the foundations that allow AI to create lasting value for members, staff, and the wider profession. As AI continues to evolve, the associations most likely to succeed may not be those adopting the latest technologies first, but those investing first in the organisational readiness needed to use them well.
