Two-Thirds of Independent Agencies Plan to Increase AI Use This Year, Survey Says

Why It Matters

The findings signal rapid AI adoption in the agency sector, but widespread governance gaps could expose firms to compliance risks and limit the technology's competitive benefits.

Key Takeaways

• 38% very likely, 30% somewhat likely to boost AI usage.
• Only 8% have AI fully embedded in daily workflows.
• 60% cite efficiency, 52% cite productivity as adoption drivers.
• 56% lack formal AI policy, raising compliance risks.
• Data privacy and accuracy top concerns for agencies.

Pulse Analysis

Independent agencies are reaching a tipping point in AI adoption, mirroring trends seen across finance, insurance and professional services. The ACT survey reveals that a combined 68% of respondents are poised to expand AI capabilities, driven primarily by the promise of streamlined operations and higher employee output. This appetite reflects broader market pressures to modernize legacy systems and meet client expectations for faster, data‑driven insights. However, the current baseline—only 8% of firms with AI fully integrated—underscores a substantial implementation gap that many will need to bridge quickly.

The primary obstacles stem from governance and risk management shortcomings. With 56% of agencies lacking a formal AI policy and more than half relying on informal peer training, the sector faces heightened exposure to privacy breaches, regulatory non‑compliance, and erroneous model outputs. Concerns about data security and accuracy dominate, echoing industry‑wide anxieties about algorithmic bias and model drift. Additionally, resource constraints, vendor confusion, and tool sprawl compound the difficulty of moving from experimental pilots to production‑grade solutions, demanding focused investment in process documentation and staff upskilling.

For agencies to translate AI enthusiasm into sustainable advantage, they must adopt structured frameworks that align technology with business objectives. Establishing clear policies, robust validation protocols, and dedicated oversight teams can mitigate risk while unlocking the efficiency gains that motivate adoption. Moreover, integrating AI with existing automation stacks—rather than treating it as a siloed experiment—will reduce change fatigue and improve user acceptance. Companies that proactively address these governance gaps are likely to outpace competitors, delivering faster client service and more insightful decision‑making in an increasingly digital marketplace.