AI: The Smartest IT Investment Your Budget Didn’t See Coming

By Kavi Maharajh, Chief Product Officer, Lumeto

Artificial Intelligence (AI) has quickly become the most talked-about technology across industries. Yet, when it comes to funding AI initiatives, organizations often struggle to find tangible ROI. The discussion tends to revolve around whether AI will replace jobs rather than how AI can be leveraged to augment existing roles and improve operational efficiency. In industries like healthcare, where demand significantly outweighs supply, AI should be viewed not as a labor replacement but as an IT investment—a strategic shift that can redefine workforce management, resource allocation, and overall productivity.

Stop Thinking Labor Costs—Start Thinking IT ROI

One of the fundamental barriers to AI adoption is the challenge of justifying its costs. Traditionally, AI-driven solutions are positioned as workforce augmentation tools, which leads to resistance due to fears of job displacement. However, in sectors such as healthcare, where there is a critical shortage of professionals, AI should be recognized as a solution to enhance capacity rather than reduce headcount.

This requires a shift in thinking—from funding AI through labor budgets (viewing it as a workforce cost) to IT budgets (viewing it as an investment in infrastructure and efficiency). In other words, AI should be seen as a tool that expands the capabilities of an already strained workforce, creating new efficiencies and reducing administrative burdens.

AI in Healthcare: More Efficiency, Less Burnout

AI is already proving its value in healthcare by optimizing time-consuming, repetitive tasks that do not require human expertise. One prominent example is AI-driven medical transcription services. Companies like Nuance (now part of Microsoft) provide AI-powered speech recognition that transcribes patient consultations in real time, dramatically reducing the administrative workload for physicians. In fact, AI-powered medical note-taking startups raised a whopping $800 million in 2024, up from $390 million in 2023—clearly, this is a trend that’s not slowing down anytime soon. Less paperwork, more patient care? Sounds like a no-brainer.

Beyond transcription, AI is being used in:

• Predictive staffing models: Hospitals use AI to analyze patient intake trends, ensuring the right number of staff is scheduled at peak hours, reducing overtime costs and burnout.
• AI-driven diagnostics: Machine learning models assist radiologists by pre-screening images for abnormalities, increasing speed and accuracy while reducing human workload. In fact, a study in the Journal of the American College of Radiology found that AI integration in radiology workflows resulted in a 791% return on investment (ROI). That’s not a typo—791%!
• Automated patient monitoring: AI-powered monitoring tools flag early signs of deterioration, allowing nurses and physicians to intervene sooner, improving patient safety and outcomes.

AI’s Glow-Up in Other Industries

Healthcare is not the only industry benefiting from AI-driven efficiency. In manufacturing, predictive maintenance powered by AI minimizes downtime by anticipating equipment failures before they occur. In retail, AI optimizes inventory management, ensuring stock levels align with demand to reduce waste and improve supply chain efficiency. AI-based automation in customer service chatbots has streamlined customer interactions while reducing the burden on human agents.

These industries have successfully framed AI as a tool for process optimization, justifying its investment through IT budgets rather than workforce cuts.

Scaling Healthcare Education with AI: Smarter Training, Stronger Workforce

The healthcare workforce shortage is not only a challenge at the operational level but also in education and training. AI can help solve this bottleneck by optimizing how healthcare professionals are trained, ultimately leading to a more robust and better-prepared workforce. Here’s how:

• Optimizing Educator Time: AI-powered assessment tools provide instant feedback to learners, reducing the administrative burden on faculty and enabling them to focus on higher-value mentoring and hands-on training.
• More Lab Time, More Experience: AI-enabled experiential learning allows learners to practice key clinical skills in scalable, simulated environments—gaining practical experience without being constrained by limited real-world clinical placements.
• More Resource Development: By integrating AI-driven training platforms, healthcare education institutions can train more students effectively, helping to address the ongoing workforce shortage.

And if you’re wondering whether AI actually saves money, consider this: broader adoption of AI could lead to 5–10% savings in healthcare spending, which translates to a casual $200 billion to $360 billion annually. No big deal, right? And let’s not forget that AI has the potential to automate up to 45% of administrative tasks, cutting annual costs by a cool $150 billion. If that’s not an IT-worthy investment, what is?

Optimizing Educator Time and Expanding Learning Without Adding Resources

As someone who spends a lot of time thinking about how to make learning more effective, I keep coming back to how we can optimize educator time by cutting down non-value-added tasks. Imagine converting existing learning content into experiential learning content in a quarter of the time it would otherwise take. Or giving educators an AI-proxy to deliver and assess learning content asynchronously—allowing learners to engage with training whenever they need it, while AI tracks their progress and performance. Even better, imagine AI providing educators with deep learner insights, highlighting common knowledge gaps so they can focus on what truly matters: the learners and their growth.

But it’s not just about making educators more efficient—it’s also about expanding learning opportunities without adding more resources. AI enables learners to spend more time in practice-based learning through scalable experiential learning environments, rather than being restricted by faculty availability. This means we can train more healthcare professionals, faster and more effectively, helping close the workforce gap without overburdening existing educators. These are not futuristic ideas—they are the practical, scalable efficiencies that AI is enabling today.

Final Thoughts: AI as Your Next Great IT Investment

AI-driven solutions are already proving their worth in improving operational efficiency across multiple industries, including healthcare. However, to fully realize the benefits, organizations must shift their perspective on AI from a labor expense to an IT investment. In healthcare education, AI’s potential to optimize instructor time, increase training opportunities, and develop more skilled healthcare professionals makes it an invaluable tool for workforce development.

Investing in AI is not about replacing jobs—it’s about expanding capacity, improving efficiency, and ultimately strengthening the healthcare system. The organizations that recognize and act on this shift will be the ones that see the greatest return on investment, both in financial terms and in overall system performance.