Many companies have invested heavily in artificial intelligence, launching pilot projects and deploying tools such as chatbots and AI copilots. However, according to an article in Harvard Business Review, most organizations still struggle to turn these experiments into meaningful business transformation. The main challenge is what researchers call the “last mile” problem—the gap between having powerful AI technology and successfully integrating it into everyday business operations.
The concept comes from logistics and telecommunications, where the final step of delivering a service to the end user is often the hardest and most expensive part. In AI adoption, the last mile refers to the difficulty of embedding AI tools into real workflows, decision-making systems, and organizational processes. Many companies have hundreds of AI pilots running, but these projects remain isolated experiments rather than becoming core parts of how the business operates.
Researchers identify several organizational barriers behind this problem. These include the proliferation of pilot projects without scaling, productivity improvements that fail to translate into measurable business results, outdated processes that AI cannot easily integrate with, and critical expertise locked inside employees’ “tribal knowledge.” Other obstacles include complex technology infrastructures, unclear governance for AI agents, and what experts call the efficiency trap, where companies optimize small tasks instead of redesigning entire processes.
The article concludes that solving the last mile problem requires organizational redesign, not just better technology. Companies must rethink workflows, capture institutional knowledge in digital systems, and create governance models for managing AI tools and autonomous agents. In other words, the real challenge of AI transformation is less about building smarter algorithms and more about adapting workplaces so humans and AI systems can work together effectively.
