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Digital EditionBusiness AI Adoption Shifts Toward Risk-Aware Approach
Business leaders are showing increased caution toward AI adoption, with those viewing it as a risk more than doubling to 11% from 5% a year ago, even as nearly two-thirds of organizations have begun testing AI solutions, according to Gallagher’s second annual Global Attitudes to AI Adoption and Risk Survey.
Initial excitement surrounding generative AI has given way to a more measured outlook among business leaders. While a significant majority—68%—still view AI as an opportunity, this represents a notable decline from 82% just a year ago, Gallagher reported.
Despite a more cautious outlook, AI adoption continues to accelerate across the business landscape. Nearly two-thirds of organizations (64%) reported in December 2024 they had at least begun testing AI solutions, up from 54% a year earlier. This progress is mirrored in investment patterns, with 60% of businesses having already allocated funds to AI initiatives over the past 12 months.
The commitment to AI extends beyond current investments, with 16% of organizations actively securing funding for future AI projects and another 15% planning to invest within the next two to three years, the report noted.
Departmental Adoption Patterns
AI implementation is occurring unevenly across organizational structures, creating a patchwork of adoption rates among different departments, according to Gallagher. IT departments predictably lead the charge, with 58% actively embedding AI technologies into their operations. Customer service functions follow at 37%, while finance departments round out the top three at 34%.
The survey identifies several departments lagging in adoption, including procurement, risk and compliance, and health and safety. This uneven distribution creates potential challenges for organizations seeking to build comprehensive AI literacy and maximize return on investment across all business functions, the broker noted.
Most organizations are still in the early stages of AI implementation, focusing on relatively straightforward applications rather than transformative use cases, per the report. The most common applications include handling customer inquiries (36%), summarizing documents (35%), and writing emails (32%).
These initial use cases represent the low-hanging fruit of AI implementation—tasks that are relatively easy to automate while delivering immediate efficiency gains. However, they also indicate that many organizations have only begun to explore AI’s potential, with more sophisticated applications likely to emerge as adoption matures and technical capabilities advance.
Key Challenges and Risks in AI Implementation
As organizations race to implement AI solutions, they face significant hurdles that slow adoption. A skills shortage stands as one of the most pressing barriers, with 30% of businesses reporting they lack the expertise to effectively implement and manage AI systems, the survey found. This talent gap creates a competitive market for AI specialists and data scientists.
Equally concerning are ethical considerations and data privacy issues, also cited by 30% of respondents. As AI systems process vast amounts of sensitive information, organizations must navigate complex questions about appropriate data usage, potential biases, and maintaining user privacy.
Compliance issues rank as the third major barrier at 27%, reflecting the rapidly evolving regulatory landscape surrounding AI technologies. With new laws and guidelines continuously emerging, businesses struggle to ensure their AI implementations remain compliant across different jurisdictions.
Risk Management Concerns
Beyond implementation challenges, organizations face ongoing risks once AI systems are operational. AI errors or “hallucinations”—instances where systems generate inaccurate or fabricated results—top the list of concerns, Gallagher noted. These errors can lead to flawed decision-making and potentially damage business operations or reputation.
Data protection and privacy violations follow closely, with 33% of business leaders identifying this as a significant risk. As AI systems process increasing volumes of sensitive information, the potential for data breaches or misuse grows proportionally.
Legal liabilities related to AI misuse round out the top three risk concerns at 31%. As AI applications expand, businesses face uncertain legal territory regarding responsibility for AI-driven decisions and actions, creating potential exposure to lawsuits and regulatory penalties.
The cybersecurity implications of AI adoption present particularly urgent challenges. John Farley, managing director of Cyber Liability practice at Gallagher, warns that businesses will face increased exposure to sophisticated attacks: “Hackers can launch really sophisticated phishing campaigns with emails that have no spelling mistakes and excellent grammar, which are very targeted to you as the victim because they pulled all your information from social media. We must get better at responding to those and then preventing those.”
Deepfake technology represents another emerging threat vector. “That’s another area where you’re going to see video or voicemail impersonations,” Farley notes. “Employees need to be trained on the new ways hackers are using AI.”
To address these evolving threats, 42% of organizations have strengthened their cybersecurity practices, while 41% are reassessing privacy and data security measures specifically to mitigate AI-related risks. As cybercriminals leverage AI to enhance their attack capabilities, businesses must continuously adapt their defensive strategies to stay protected.
People-First Strategies for Successful AI Integration
As organizations rapidly integrate AI into their operations, a clear emphasis on protecting and developing their workforce has emerged. An impressive 85% of businesses have introduced job protection strategies as part of their AI adoption framework, Gallagher reported.
Nearly half (45%) of surveyed businesses are offering training programs specifically designed to upskill employees on AI tools. Meanwhile, one-third have committed to reskilling employees whose positions have been displaced by AI technologies, reflecting a growing belief that AI will augment rather than replace human roles.
Ben Warren, managing director and Head of Digital and AI Transformation at Gallagher, emphasizes that communication about AI risks cannot be a one-time effort.
“There’s fear among some employees, who are asking, ‘Is AI going to take my job?’ and ‘Are we all going to be automated away?’ The noise is making some people quite despondent about change and embracing the opportunities with AI,” says Warren. “So, how do you bring employees on that journey? You need to set clear AI governance and guardrails, drive AI literacy and ensure there’s an ongoing change management program to support the transformation.”
The AI revolution isn’t just transforming existing jobs—it’s creating entirely new one, according to the report. One-third of businesses report creating new AI-specific positions to bring in specialized expertise, the survey found. These emerging roles include AI product managers, data scientists, AI specialists, and executive positions dedicated to overseeing AI strategy and implementation.
View the full report here. &
