Opinions expressed by Entrepreneur contributors are their own.
Key Takeaways
- Most leaders assume AI’s biggest value shows up in bold, high-visibility initiatives — but that’s not where the strongest returns are emerging.
- The companies seeing measurable impact from AI aren’t chasing headlines; they’re applying it in places many competitors still overlook.
AI isn’t just for players in tech-heavy sectors. Businesses across the economic spectrum — even those in traditionally low-tech environments — can make substantial strides in productivity and innovation by embracing AI.
A common perception is that AI adoption requires specialized data scientists or massive upfront infrastructure investments. In reality, the true value of modern AI lies in its ability to solve common, costly operational challenges that affect nearly every organization. AI can analyze vast amounts of data far faster than human teams, delivering predictive insights that optimize supply chains, streamline administrative work and improve decision-making across departments.
The real challenge is knowing where to begin. The AI landscape can be overwhelming, and many executives remain unfamiliar with how to apply it effectively. According to HR Dive reporting, 58% of C-suite leaders have never undergone any AI training. That knowledge gap leaves many organizations at a disadvantage when it comes to leveraging AI to improve performance and outcomes.
The key is identifying specific areas where small efficiency gains can translate into meaningful improvements in profitability and growth. One of the best ways to start is by examining how other organizations have successfully integrated AI into their workflows to accomplish more without sacrificing momentum or market share.
1. Lean into AI to fill gaps in the project lifecycle
Every company manages short-term, medium-term, and long-term projects. Regardless of what you call them, most projects include friction points that could benefit from AI support.
Successful project execution isn’t just about organizing tasks; it’s about ensuring that knowledge and data flow seamlessly as teams evolve and timelines shift. For example, AI-powered project management platforms like Digs act as centralized, tech-enabled repositories for every stage of a construction project, from initial concept to end-user handoff.
Rather than simply tracking progress, these tools integrate historical project data to surface potential schedule risks and automatically flag documents that may impact milestones. By adding a predictive layer of intelligence, AI streamlines execution, improves accuracy and reduces the need for constant human oversight. In industries facing significant labor shortages and coordination challenges, this approach helps remove barriers to timely, reliable delivery.
You don’t need to implement AI across every initiative at once. Start by identifying repeatable, multi-step processes within your organization. Then explore AI tools that can address the specific gaps that consistently slow your team down.
2. Use AI to create more consistent employee training
As businesses grow, uneven training often becomes a hidden obstacle. When some employees receive more in-depth instruction than others, it creates performance imbalances that limit overall productivity and consistency.
AI-enhanced learning management systems (LMS) offer a scalable solution. Moving employee training to an LMS platform ensures standardized content delivery and clear progress tracking, reducing the inconsistencies that stem from ad hoc or informal training methods.
Organizations can begin by auditing their existing training materials and identifying core knowledge gaps. From there, they can pilot a basic internal LMS by digitizing and testing required modules before investing in more advanced solutions.
The most sophisticated platforms extend beyond simple delivery and tracking. They analyze individual learning patterns to personalize content and, in some cases, match employees with mentors based on development needs. This not only strengthens knowledge retention but also encourages more effective information sharing across teams.
A better-trained workforce is a more capable workforce — and one less vulnerable to knowledge loss when employees move on.
3. Reduce workload duplication with AI oversight
Work duplication is one of the most common — and least visible — drains on productivity. When employees unknowingly repeat tasks or redo completed work, timelines stretch and resources are wasted.
This challenge is especially pronounced in healthcare, where legacy systems and manual documentation remain common despite high-stakes outcomes. Duplication of effort can cause delays, communication breakdowns and unnecessary administrative burden.
To address this, many healthcare organizations are turning to AI copilots and intelligent agents. These tools can identify when a task has already been completed, prevent redundant work and even execute routine steps independently before notifying the appropriate human stakeholder.
Even if duplication isn’t immediately visible within your organization, it likely exists. Evaluating where overlapping responsibilities occur is a valuable first step toward using AI to eliminate unnecessary repetition and improve operational flow.
Your business may operate in a traditionally low-tech environment, but the efficiency and productivity gains enabled by advanced AI systems are broadly accessible. By systematically targeting operational bottlenecks — whether in project management, training or task coordination — you can introduce AI in focused, practical ways.
The result is a more efficient, resilient organization positioned for sustainable growth in an increasingly competitive market.
Sign up for the Entrepreneur Daily newsletter to get the news and resources you need to know today to help you run your business better. Get it in your inbox.
Key Takeaways
- Most leaders assume AI’s biggest value shows up in bold, high-visibility initiatives — but that’s not where the strongest returns are emerging.
- The companies seeing measurable impact from AI aren’t chasing headlines; they’re applying it in places many competitors still overlook.
AI isn’t just for players in tech-heavy sectors. Businesses across the economic spectrum — even those in traditionally low-tech environments — can make substantial strides in productivity and innovation by embracing AI.
A common perception is that AI adoption requires specialized data scientists or massive upfront infrastructure investments. In reality, the true value of modern AI lies in its ability to solve common, costly operational challenges that affect nearly every organization. AI can analyze vast amounts of data far faster than human teams, delivering predictive insights that optimize supply chains, streamline administrative work and improve decision-making across departments.
