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  1. Workplace News & Trends
  2. AI Adoption Strategy: Why Timing Beats Being First
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Blog

AI Adoption Strategy: Why Timing Beats Being First

August 19, 2026 | Sarah Murrow

Editor's note: Posts published on From the Workplace are written by outside contributors and do not necessarily reflect the views or opinions of SHRM.

Companies are in a high-stakes race to prove they are leaders in adopting artificial intelligence. The pressure is immense, and the headlines are alluring. But in this rush, many business leaders are forgetting a crucial lesson: being first isn’t always the same as being the best.  

We’ve seen this play out with consumer technology. Early adopters of smartphones or streaming platforms contend with glitches and inefficiencies that are ironed out for later users. Rushing to be first carries risks that careful, strategic followers can avoid. As a leader in risk management for more than 20 years, I see immense value in being a fast follower — not falling behind, but ensuring your business isn’t moving too quickly without the right safeguards.

The perceived benefits of being an AI pioneer are clear: positive headlines, a reputation for innovation, and a potential competitive edge. IBM’s Institute for Business Value report found that 77% of executives believe they need to adopt generative AI quickly just to keep up with competitors. This rush overlooks inherent risks of implementing AI tools. Many solutions are still in beta versions, delivering unpredictable results with incomplete safety guardrails. Implementation can cause operational disruptions, slow down workflows, and lead to expensive reengineering. Failed pilots can cause reputation damage, making companies look careless rather than visionary.   

It’s no surprise that the same IBM survey found that 45% of business leaders cite concerns about data accuracy or bias as a major obstacle to adopting AI. These are not small issues. When companies implement AI tools without appropriate testing, oversight, or planning, the consequences extend beyond inefficiency; they can undermine trust with customers, employees, and regulators.

This is where the advantage of being a fast follower becomes clear. By letting others lead the charge, you can learn from their mistakes and avoid the pitfalls they encounter. As the technologies mature, costs stabilize and vendors refine their pricing models. You can wait until applications demonstrate a clear return on investment, allowing you to adopt proven use cases.  

Internal adoption improves when employees see that new tools are reliable. Workers who are trained and empowered to use AI become partners in innovation. At Allianz Trade, we’ve found that the most successful transformations come not from racing ahead, but from integrating new technologies thoughtfully.

Toolkit: AI Field Manual for Employers: 138 Use Cases for AI at Works

To achieve this, leaders should first develop a comprehensive AI strategy framework before making any significant investments. This means clarifying the specific business goals AI should support and setting clear metrics to measure success.

The best approach to developing this strategy is to start small and scale intelligently. Pilot AI in non-critical areas to gather data on its effectiveness and safety before expanding. Be mindful that what works in one market may not translate to another.  

An effective AI strategy means that investment must also extend to people, not just technology. Training employees on AI literacy is critical for building comfort, trust, and a culture where teams can identify potential use cases from the ground up. It’s crucial to emphasize AI as a complement to human expertise, not a replacement. Use AI to enhance human decision-making and reinforce a culture that values innovation and experience.

As you scale, building strong governance and risk oversight is paramount. Establish clear policies on data use, compliance, and ethics, and create a cross-functional oversight committee with representation from IT, legal, operations, and HR.  

Sample Policy: Customizable AI Governance Policy Template

True leadership in the AI era isn’t about who adopts first. It’s about who adopts best. The goal is not to chase every innovation, but to embed the right ones with purpose, structure, and foresight. Residence and confidence in this new era belong to those who move smartly: companies that balance innovation with prudence, boldness with foresight, and technology with trust. 

Because in AI, as in business, timing is everything.

Sarah Murrow is the president & CEO of Allianz Trade in Americas.

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