Burp! Tech Mahindra, AI and the metabolic rate of change

A few years ago, McKinsey developed a framework known as 'organizational metabolism' to assess an organization’s capacity to digest change and adapt to the market. 

The idea has recently been extended by consultant Alicia Rule who has been talking about what she calls the metabolic rate of change on LinkedIn. The metaphor is used by her to frame diagnosis of some of the change fatigue organizations are suffering as they adopt AI. Symptoms of AI indigestion include decision fatigue and cognitive overload as initiatives mushroom but are never completed, pilots don’t scale and strategic documents are divorced from daily reality. 

But how is technology evolving from a business “enabler” to become the very viscera of the enterprise and its strategy. In the view of Harshul Asnani, Tech Mahindra’s President for Europe,  AI is having its coming-of-age moment.Having moved through the hype cycle and overcome human fear, he is confident organisations are now poised to reach value realisation from the technology:

Organizations that are pulling ahead are redefining the way decisions are made and how accountability is distributed – it means a shift in organizational structure. AI requires organizational metabolism. Companies that stop thinking about what AI can do and instead start thinking what are we willing to let go? They will get ahead. Companies need to let go of the old way of functional workflows and old designs.

2026 is a moment of truth – you need a lot of nerve in leadership and should take the bull by the horns by redesigning the processes and the governance. Governance is a big performance metric for trust and regulatory readiness. Think of it less as a compliance overhaul and more as a competitive differentiator. We need leaders with the courage because we are at an inflection point.”

It might be thought that this is easier for smaller start-ups to achieve as opposed to large enterprises. Asnani disagrees, arguing that the largest enterprises will see a more profound impact, but this is less down to organizational size and more about the willingness to make the organizational changes. Examples of very large companies doing it successfully, according to Asnani, are the digital natives: Amazon, Netflix, Tesla and Revolut in UK. He believes they are able to move faster because their strategy is tied to their platforms.

However, he sees traditional companies also modernising to be able to digest AI. They include banks re-building on cloud-native platforms; telcos moving to provide autonomous networks; software defined auto manufacturers striving to make cars safer (such as Mahindra itself in India); as well as retailers using dynamic pricing and understanding customers better. He adds: 

The C-Suite needs to look at this more from a business outcome perspective, technology is just available like electricity. We are working on 100 AI programs across the customer base. Of these ten percent have a roadmap with defined use cases; 20% have no clue and are in fear mode, not knowing where to start and may fall by the wayside because of this. We are thinking through use cases with them in non-mission critical areas. Around 70% are in the middle showing a bit of fear and a bit of optimism and are learning from the more advanced players. We are doing more consulting here working with them on first projects in supply chain or customer support.

Re-coining the SI role for AI

Evidently the system integrator community itself is living through the need to metabolise change, while assisting clients with the same challenge. Asnani observes that:

Tech services companies (SIs) need to pivot to become the backbone of enterprise AI adoption. We need to move from being implementers to orchestrators. We need to re-coin who we are...2025 will be the last financial year where the industry grows in lockstep with the number of people. Revenue will grow but BPO and software development will largely be delivered by agents/digital colleagues.

Asnani believes that clients are becoming far more receptive to contracts linked to outcomes so that pricing is not tied to transactions but rather to revenue share or gainshare. Tech Mahindra is pioneering some of these models with customers. 

The contractual shift is required because the nature of the work is changing as SIs are building agents and a new ecosystem of partners for accelerated value creation. Asnani expands:

In the past we did not charge customers for us to train humans, with agents we are charging to build and train them, but once they are fully deployed there is no charge. In this way we are bringing the automation and productivity to bring down the customer’s cost.

SIs need to pivot quickly because the traditional ways of working are going. Once AI is adopted at scale the technology intensity of every company will shift from an average of four percent revenue spend to 15-20% of revenue spend and so we need to follow the money, which requires a mindset change and organizational metabolism.

My take

From the discussions I am having with SIs and consultants, it is clear that these players have a big role to play in helping many enterprises create value from their adoption of AI. They are required to support change management and, with apologies to McKinsey and the straining metabolic metaphor, helping to 'burp' the enterprise struggling with new-born AI indigestion. They are pivoting to become the independent experts bringing together humans and digital agents, rethinking workflows and governance, as well as orchestrating the SaaS agents heading into the enterprise this year and next from all our favored software vendors.