#32 - At Process: Transforming Healthcare Through AI and Process Improvement.

Dr. Krishna Vedala, host of the Connected by Health podcast, interviewed John Thomas and Landon Arnold about their backgrounds in process improvement, artificial intelligence, and enterprise operations. Thomas has two decades of experience in enterprise operations, intelligent automation, Lean principles, and Six Sigma. Arnold has worked in consulting and large enterprise environments, helping organizations identify inefficiencies, redesign workflows, and improve how work gets done. Their shared experience led them to focus on the practical relationship between process improvement and AI.

The discussion, led by Dr. Krishna Vedala, highlighted that At Process was created to offer organizations a more collaborative alternative to traditional consulting. After witnessing failed projects and strained client relationships in large consulting firms, Thomas and Arnold wanted to build partnerships in which clients were treated as collaborators rather than cost centers. At Process is a Chicago-based boutique AI solutions firm that primarily serves small and medium-sized businesses. Its goal is to deliver practical value by reducing inefficiencies and improving operations.

At Process follows a process-first methodology. Before introducing AI or automation, the company maps the existing workflow, examines the interaction between technology and human behavior, identifies inefficiencies, and redesigns the process. The team emphasizes that successful AI implementation depends heavily on planning, with much of the work involving an understanding of how information moves through an organization. Lean and Six Sigma principles help distinguish value-added activities from unnecessary work before technology is applied.

During Dr. Vedala's interview, Thomas also explained the difference between traditional chatbots and agentic AI. Chatbots generally respond to individual prompts, while agentic AI operates proactively by following defined goals, rules, and objectives. It can make decisions, learn from situations, and coordinate activity across multiple systems. This capability is particularly valuable in healthcare, where disconnected enterprise systems and manual workflow gaps create significant administrative challenges.

Dr. Krishna Vedala and the guests identified healthcare's administrative burden as one of the most important areas for AI improvement. AI could support intake, scheduling, documentation, and other tasks, allowing clinicians to spend more time with patient