As businesses continue to navigate the landscape of artificial intelligence (AI), a recent examination of corporate strategies reveals three distinct trends that are shaping the future of AI adoption. Throughout 2025, discussions with various business leaders highlighted how the successful integration of AI often hinges on a clear understanding of the problems to be solved, rather than a mere focus on the technology itself.
The first trend observed is a significant increase in the use of AI for back-end tasks. While many organizations are drawn to the flashier applications of AI, such as chatbots, it is often the mundane, administrative functions that provide the most substantial benefits. For example, law firm Troutman Pepper Locke has implemented AI in various forms, including an internal chatbot, but has found greater success in utilizing AI for back-end administrative tasks. Chief Innovation Officer William Gaus noted that during a recent merger, their AI capabilities drastically reduced the time required to update the bios of 1,600 incoming attorneys from six months to a streamlined process, saving approximately $200,000 in labor costs.
The second trend emphasizes the critical role of personnel in the AI transformation journey. Executives across industries have pointed to “change management” as a vital aspect of successfully integrating AI within their organizations. As companies deploy new AI tools, the readiness and adaptability of employees become central to the initiative’s success. Honeywell has approached its AI strategy meticulously, with CTO Suresh Venkatarayalu explaining that every AI effort begins with identifying measurable use cases that add value. This strategy has led to an increase in generative AI projects across the company, with 24 initiatives currently in production and more on the horizon.
Conversely, many organizations experience what Erik Brown, AI lead at consulting firm West Monroe, describes as “AI fatigue.” Companies that prioritize technology over clearly defined challenges often find themselves wasting resources on unproductive projects. Brown recounted a scenario where a client’s innovation group failed to yield results because the focus was placed on AI for its own sake rather than on solving specific business problems. By realigning their efforts to address actual challenges, the client discovered viable AI applications that improved their operations.
The third trend revolves around the importance of leading with a problem-solving mindset rather than a technology-first approach. BigRentz, a construction equipment rental firm, exemplifies this principle. CEO Scott Cannon explained that while they did not initially plan to build their business around AI, it emerged as the most effective tool to resolve their operational challenges. By leveraging traditional machine learning techniques rather than the latest generative AI trends, BigRentz demonstrates that finding the right solution for a problem can often yield better results than chasing current tech fads.
In the healthcare sector, a similar story unfolds. Although many attempts to create standalone AI-driven health companion chatbots have seen limited success, AI applications in back-end processes are gaining traction. Medical professionals are increasingly using large language models (LLMs) to streamline administrative tasks, such as transcribing conversations with patients and generating medical documentation, ultimately freeing up more time to focus on patient care. Wiljeana Glover, a researcher at Babson College’s Kerry Murphy Healey Center for Health Innovation and Entrepreneurship, noted that these administrative enhancements are where AI is making rapid progress.
As organizations continue to refine their AI strategies, maintaining a focus on people remains paramount. While AI’s impact on employment dynamics is still unfolding, the immediate effects on job roles, hiring processes, and employee training are becoming increasingly clear. Balancing enthusiasm for AI with the realities of workplace changes is crucial for fostering a positive environment. Sheila Jordan, Honeywell‘s SVP and Chief Digital Technology Officer, cautioned against underestimating the importance of employee engagement in AI adoption.
As businesses prepare to advance their AI initiatives into 2026, it will be essential to find the right balance between leveraging technology and maintaining a skilled workforce. The forward-looking sentiment shared by industry leaders emphasizes that understanding the problems AI can address while keeping employee concerns at the forefront will be instrumental in shaping effective AI strategies moving forward. The interplay of technology and human elements will ultimately define the success of AI in various sectors.
For further insights into AI applications, visit IBM, OpenAI, and Microsoft.
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