CEOs and boards need to determine whether AI can help them achieve their value creation goals in healthcare-related businesses. U.S. healthcare with its $5T scope and exabytes of data presents an attractive AI transformation target. In fact, In June 2024, Silicon Valley Bank reported, “One in four dollars invested in healthcare companies is going to companies that are leveraging AI.” The hype around AI has been extraordinary and historically, heavily hyped innovations have turned out to be more narrowly useful than hoped. AI, however, is unique and, even after the hype dissipates, is likely to have an impact akin to that of software, the internet, or mass production.
Like previous payment technologies adopted by large enterprises, the benefits cannot be only about speed; they need to also be about efficiency and reliability. By adopting these technologies, healthcare providers can reduce administrative burdens and focus more on patient care rather than paperwork. One of the strongest initial use cases of accelerated payments has been reducing employee payroll cycle time. In an era where healthcare workers are scarce and in high demand, improving the payroll experience affecting these employees could be a catalyst for adoption of faster payments in the healthcare industry.
AI is unlike previous automation efforts because it is not rules-based and thus does not need to anticipate every use case in terms of inputs, environmental conditions, or outputs. AI achieves this by using data models and algorithms which outwardly mimic human abilities to absorb and apply information autonomously. An AI model then is like an assembly line for the real-time mass production of knowledge worker “assistants” increasing the supply of knowledge work. Greater supply will reduce prices enabling better healthcare outcomes at lower cost. According to a 2024 McKinsey study, early adopters of AI have identified seven promising market segments:
AI transformation is difficult, and results take time. As of July 2024, 58% of healthcare firms striving to use AI, all subject to sponsorship bias, reported achieving positive ROI, yet most had not quantified the ROI. This reflects both the newness and the difficulty of AI. Firms will raise their probability of success if they approach AI as an enterprise-wide transformation like the introduction of Six Sigma, a new ERP system, or offshoring. Thus, culture, training, strategy, resources, and investment must be aligned and effectively governed. Success starts with setting a SMART goal for the program, e.g. “Increase yield on appeals of denied medical claims by 20% while reducing the cost per appeal by 15% relative to baseline within 24 months.” Evaluation of the investment need, capabilities of the firm and ROI requirements of shareholders can then inform final go/no-go decision making. Once a “Go” decision is made, firms will benefit from deploying best practices in enterprise change leadership.
The value creation potential of AI is exciting and realizing it is challenging. CEOs and boards who succeed will deliver better revenue growth, profitability, customer engagement and valuation multiples than their non-AI competition. This is predictable based on the high probability that these firms will couple better current performance with the ability to innovate more rapidly and capital-efficiently than competitors. The AI transformation journey is one for the bold and those who couple prudence with their boldness will be the winners.
Rob Pinataro has 25 years of SaaS, fintech and healthcare leadership experience, focusing on business strategy, innovation, transformation and growth. He recently led Payspan as COO then as CEO through two PE exits raising over $330M in capital. Rob currently serves on the boards of Connexure, Atlanta’s Technology Executive Roundtable, Cassandra Official Music Global, and the Advisory Council of Georgia’s USO. He advises PE firms on fintech/ healthcare investment opportunities and value creation through better execution of digital and cybersecurity strategy.