Ryan Sousa is vice president of the data, analytics and artificial intelligence practice at Pivot Point Consulting, a health IT consulting firm. (It was ranked No. 1 Best in KLAS for Managed Services and Technical Services in 2024.) His background and expertise in AI and analytics is extensive. And when asked to look ahead to 2025 in health IT, he has a lot to say on these two technologies so important to healthcare.

Sousa predicts big things for generative AI, a new way of delivery for AI and analytics, and using the two technologies in tandem to drive growth. We interviewed him on the subject of next year, and this is what he had to say.

Q. You say in 2025 genAI will come into its own, creating potential for significant savings. How is this going to happen?

A. In 2025, genAI proof-of-concepts and pilot programs will start to demonstrate positive impact and value for healthcare organizations, which will begin to explore how they can defer new or sunset existing product investments by doing it themselves.

Areas such as diagnostics, patient flow optimization, and administrative tasks like billing and supply chain benefit the most from genAI due to its ability to analyze structured and unstructured data to generate predictive and prescriptive insights.

These early successes will drive organizations to rethink traditional approaches to technology investment, allowing them to defer new product acquisitions and phase out legacy systems in favor of building customized systems in-house.

This adoption of genAI will not be without its challenges. Healthcare organizations will face hurdles like data privacy and ethics concerns, regulatory compliance, integration with existing systems, and the need for workforce and patient education.

Addressing these challenges will require robust, scalable data governance policies, investments in cybersecurity measures, strategic planning for technology integration, and comprehensive training programs to adapt to new tools and workflows.

By harnessing these advanced capabilities, health systems will unlock unprecedented gains. Automated coding can significantly reduce errors and processing times in claims management, leading to faster reimbursements and lower administrative costs.

Census prediction enables better resource allocation and staffing decisions, improving operational efficiency and patient care delivery. As efficiency improves, patients will experience reduced costs, shorter wait times and higher-quality care due to more effective use of resources and personnel.

The ongoing migration to the cloud, with its scalability, data-sharing capabilities and computational power, is the cornerstone of this transformation. Cloud infrastructure supports the vast data storage and processing needs of genAI applications, facilitating seamless integration into existing workflows.

However, this transition raises security concerns, particularly around data breaches and compliance with healthcare regulations like HIPAA. Also, organizations will need to learn how to leverage the vast tools available to innovate with data while also learning how to excel in fin-ops to do this cost-effectively.

Q. On another front, you suggest a new way of delivery for analytics and AI will take hold in 2025. What is it, and what would it mean for healthcare?

A. Legacy centralized, transactional approaches to analytics and AI delivery that are rigid, top-down and project-oriented will give way to a federated and collaborative model. The legacy approach is designed for a more static environment and struggles to adapt to the dynamic needs of today's ecosystem of care.

By contrast, the federated collaborative model empowers decentralized teams to make agile, real-time decisions. This shift is not only a response to technological advancements but also a cultural transformation, emphasizing trust, autonomy and cross-functional collaboration.

Adopting a bottom-up decision-making structure aligns analytics and AI initiatives more closely with the immediate needs of care providers and patients. It allows for more customized and context-aware systems, addressing specific challenges in different departments or units.

Such an approach facilitates faster delivery of data products, minimizes bureaucratic delays and fosters innovation by encouraging structured experimentation at all levels of the organization.

From an operational perspective, federated models can lead to significant productivity gains. Employees empowered to make decisions and contribute meaningfully to initiatives are more likely to be engaged and satisfied in their roles. This enriched work environment not only boosts morale but also helps attract and retain top talent in an increasingly competitive industry.

This model is not without challenges. Organizations must invest in robust, flexible data governance frameworks to ensure consistency, security and compliance across decentralized teams. Additionally, fostering a culture of collaboration and continuous learning is essential to realize the full potential of this approach.

That said, those who can overcome these challenges will thrive, while those who don't will struggle to keep up.

Q. One more peek ahead at 2025: You say leading organizations will leverage analytics and AI to drive growth. How will they accomplish this?

A. With the growth in competition driven by new players and mergers and acquisitions, there will be significant pressure to harness analytics and AI to reduce cost and improve profitability by driving waste and redundancy out of the system.

Leading organizations will balance this ruthless cost reduction focus by leveraging analytics and AI to promote growth and greater profitability – improving outcomes and enriching the patient and provider experience along the way.

Analytics and AI are not only tools for cutting costs – they are powerful drivers of growth that contribute to profitability. A prime example lies in AI-enabled personalized medicine. By analyzing vast amounts of patient data, AI can help tailor treatment plans to individual patients, leading to better clinical outcomes and increased patient satisfaction.

For instance, healthcare organizations that use AI to optimize cancer treatment pathways can enhance patient recovery rates while strengthening their reputation as leaders in advanced care. Similarly, predictive modeling in revenue cycle management allows organizations to identify financial bottlenecks and improve revenue collection, creating new growth opportunities.

Balancing cost reduction with investments in growth initiatives is critical for sustainable success. Leading organizations achieve this balance by reinvesting the savings from efficiency gains into innovative projects that enhance their strategic positioning.

These organizations leverage analytics to streamline operations while simultaneously investing in cutting-edge research and patient-centered care initiatives. This dual focus has driven operational efficiency and improved patient experiences, enabling the organization to achieve sustainable growth and profitability.

Looking to the future, several emerging analytics and AI technologies will be crucial for healthcare organizations to stay competitive by 2025. Technologies such as generative AI for clinical decision support, real-time predictive analytics for operational management, and AI-driven digital twins will become increasingly important.

Digital twins, for instance, enable healthcare organizations to simulate and optimize hospital operations, predict patient flow, and test new care delivery models in a virtual environment. However, perhaps the most transformative focus area will be achieving true interoperability – seamlessly connecting disparate data sources across the healthcare ecosystem.

This will allow organizations to generate holistic, actionable insights, ultimately improving care coordination, reducing costs and driving better patient outcomes.

Healthcare organizations that successfully balance efficiency-driven cost reductions with growth-oriented innovation will emerge as leaders. By strategically leveraging analytics and AI, they will improve their financial health and create a more patient-centered and provider-friendly healthcare ecosystem.