50 Innovators of the Year 2021
The increasing volume of data and insights has made decision-making a complex and time-consuming activity for organizations today. Technology, specifically AI, can manage such complexity and evolve your decision systems and processes to compete in the digital landscape and achieve digital scale.
AI is able to achieve this by inferring decision-making rules, both latent and manifest, from historical data, find insights from historical data and applying these rules consistently and accurately to enable autonomous processes. The best part? AI keeps getting better as it continually learns from data, decisions, and actions.
To understand how AI transformations are helping organizations, esp. healthcare ones, innovate and respond to emerging market dynamics, let’s talk to Nikhil Mendhi, the COO of Exponential AI.
Q: Nikhil, these last few years have been good for AI; there’s been a rise in adoption. But, there’s also talk of how tough it is to see ROI on AI. So tell us about the challenges that organizations face in seeing value from AI and what needs to be done.
It’s true that organizations sometimes face challenges with their AI programs. Usually, it’s due to lack of clear AI strategy, no business buy in, gaps in getting the right talent, stakeholder trust issues, or other technical challenges around productionizing and scaling AI solutions.
To solve for this, the first thing organizations need to do, is to assess how AI can be better leveraged to drive actions and outcomes. This can be made possible when Decisions, becomes the focal point of their AI transformation efforts.
There’s a tremendous opportunity for processes across customer engagement, operations, and finance to be transformed to deliver better cost and quality outcomes with the adoption of Decision Intelligence.
Q: Gartner recognizes Decision Intelligence among its top 10 trends that will drive the future of AI. It seems like we already see a paradigm shift towards decision intelligence (DI) within the AI industry. Nikhil, you also spoke about challenges with design and production; tell us more.
While AI promises great results, it’s quite a struggle to get there. Organizations face challenges with solution design, model orchestration, and productionizing, and often have little clarity on expected value and time-to-value. You will be surprised to know that 90% of all machine learning models never even make it to production.
Much of this can be fixed by what I said earlier - picking the right focus. Decision intelligence with its inherent focus on decisions, and decision outcomes promises clear, quantifiable value from AI.
Which is why, to help organizations overcome such challenges and build functioning and scalable AI for themselves, Exponential AI offers an Enterprise-grade Decision Intelligence Platform, ENSO. ENSO, let’s businesses create value in production in less than 3 months.
Q: Interesting, can you expand on that and tell us more about how you are able to do this with ENSO.
Let me explain how this happens. When we engage with a client, once we discover the use case, we use a platform-driven approach and turn-around production-ready solutions that can show clear success in a 10-14 weeks timeframe. Accelerated delivery is made possible because we focus on decisions, deconstructing processes into constituent decisions and enabling autonomous actions at each decision point using decision agents. Decision agents are at the root of all this, they enable faster solutioning, orchestration and production for us.
Q: Can you please elaborate on Decision Agents? You say these agents help build solutions faster and better. How does that happen?
Decision agents are AI-enabled digital workers pre-trained to make decisions like human experts. Decision agents use multiple AI and rule-based decision-making techniques to make trusted, reproducible, and transparent decisions. One or several decision agents can make up an AI solution.
A solution can be built by selecting and assembling pre-built, pre-configured, domain-specific decision agents on ENSO. ENSO solutions can be trained and customized to the organization’s own data for more relevant and contextual decisions. The platform also enables a solution or its constituents (agents) to be reused in other solutions within the enterprise -which means adoption and scaling are easy.
Q: Other factors influence the success of AI - operational culture, for instance. How does Exponential AI manage to understand a company’s operational culture before strategizing a solution for them?
Operational culture, as you hint upon, is always different from one company to another. How much it influences our approach to a solution depends on the degree of AI maturity within the organization. Mostly, we use a mix of art and science to understand our client’s needs better.
On the art side, our deep expertise of engaging for decades with healthcare and financial services organizations, knowing operations as former operators ourselves gives us a good sense of clients’ readiness for the transformation and ultimately enables decision-making with AI.
On the science front, it is more of looking into the operations, their KPIs, and their level of operational debt. Here, we try to understand and map out the process to be transformed in detail including how it integrates into the value chain. We then determine which technology or technique needs to be applied to accelerate transformation and drive business value.
When required, we request the client for sample data, run it through our platform, and present a quick POC.
To put it simply, strategizing a solution needs balancing out culture and operational debt, and blending the art and science.
Q: Lastly, tell us what industries and use cases have seen successful outcomes from decision intelligence and ENSO?
Our primary focus has been on healthcare, and we have seen fantastic results across Claims Processing, Payment Integrity, Contract Management, Utilization Management, Adverse Event Reporting Automation, Clinical Trials etc.
The Leader Upfront
Nikhil Mendhi, COO: Nikhil has spent 15+ years leading high-growth ventures. He has successfully led large-scale transformations and enterprise-wide initiatives for Fortune 500 Conglomerates in the U.S., South America, Middle East, and Asia. He has extensive experience in transforming operations, product development, platform delivery, strategic planning, and change management. Before Exponential AI, Nikhil was Vice President and Practice Leader at HM Health Solutions, a Highmark Health growth venture, where he led delivery of large-scale transformations and product development with high client satisfaction.