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Leadership Re-imagined – The Future through AI lens

Umesh Sethi  
Director of Project Management, Fluree
Umesh Mohan Sethi, is a Product leader in the Data and AI space with around 17 years’ experience in IT and more than 10 years’ experience in B2B SaaS. He has had the privilege to work with highly agile startups in Data and AI sphere as well as MNCs in Consulting and Ecommerce. Apart from AI & Data, his interest includes areas such as Fintech and E-commerce.

We live in a time when almost every other business news seems to be about AI and its impact – direct or indirect, in our lives. In any event, the need to embrace AI seems to be very real & inevitable now. Artificial Intelligence, starting from simple Machine learning – to the latest Generative AI models is helping organizations in multiple spheres.

These are areas such as automated Data Discovery, inbound and outbound marketing, managing customer satisfaction through chatbots, process and software automation, governance and risk management.

Meanwhile, a question which seems to have gotten ignored – but is extremely important is: how Leadership needs to guide AI adoption to create sustainable value for their organizations.

In my opinion, five strategies will enable leaders to make use of AI judiciously and drive long term value to their organization & customers.

 

    1. 1. Change Management & Culture of Learning:   An Organization’s talent base is perhaps its most important resource. Regardless of the efficiency or power that any AI brings, it is very important to ensure that the talent base is motivated and keeping pace with the changes in the company. Transitions, cut-backs and organization changes that will inevitably happen due to AI need to be communicated properly and senior and mid-management need to be re-skilled wherever feasible to embrace new business processes due to AI. Otherwise, you may end up having a Jet engine in your car but no navigation and steering mechanism to handle that!

 

    1. 2. Long Term AI Roadmap:  I have seen Department leads, SBU heads, middle management etc. sponsor small to mid-scale AI projects which create some impact in the way the products or services of the organization are consumed. However, there is an increasing need to deliberate on ‘What is our long-term Roadmap for AI? ‘ in top management and strategic meetings at a portfolio & organization wide level.  Please remember the incremental theory of gains. Miniscule gains in efficiency, cost reduction in one-department when combined with gains in another may multiply rather than just add up – which is only possible with cross-team and portfolio level collaboration.

 

    1. 3. Decision Chain Contraction:  Similar to the supply chain for Logistics, we also have a Decision Chain in any organization or if I expand further – we have an ‘idea to execution’ chain. A question which any leader needs to keep asking, is whether their AI strategy has shortened this decision chain.    In today’s world, its not just the lead time of groceries arriving at our table that is shrinking, but everything else as well:  GTM plan timelines are shrinking, customer’s patience is shrinking, TATs across business processes are shrinking. Leadership needs to apply AI in a strategic way to shrink their decision processes from legacy-months to new-age weeks to reap the long term rewards of AI.

 

    1. 4. AI Architecture & Governance: As someone from an AI product organization, I have witnessed first hand the benefit that organizations derived by putting in place a comprehensive AI architecture and Governance layer for their AI systems. For instance, is it micro-services that will run your AI across multiple business processes if they are tightly interlinked. Similarly, what is the governance strategy / approval workflow that systems will use with AI recommendations. Leadership needs to remember that AI will never be a pilot of their organization, and will at best be a reliable co-pilot that requires governance processes and risk management controls.

 

  1. 5. The Bharat Stack: I talk about the Bharat or India stack because its my country, but really what this means is that each region, each country may have its own set of challenges, own set of legislations, technology imperatives. What may work in the West may not necessarily work elsewhere. An example is how Bharat harnessed UPI and ONDC for amazing growth in digital and payments. Even in the case of AI, leaders in India are beginning to adopt AI with their own innovations; either by tweaking the cloud stack, creating their own Infrastructure, language localisation and a lot more. Leaders will need to be mindful of where their users and customers are and evolve their AI stack accordingly.