AI Startups :Face-off with the Big 5s

Should a true AI engine be industry focused or industry neutral to have a positive effect on company valuation? This is one of the key debates amongst the VCs & PE firms evaluating their investment options in the promising world of AI startups.

Technology startups are often categorised by analysts to fit into well defined industry sectors. But the same principle cannot be applied to the world of AI. 

A real AI engine should have the agility to rapidly self-learn and adapt itself to any industry sector within weeks and drive valuable insights and predictions for the core functions of that industry. 

The Big 5s, with the DNA of industry-aligned organisation structures, have also been making appreciable  investments in AI to demonstrate value beyond their core people based consulting model. However, there is no reflection of that AI finesse from the Big 5 as they seem to be burning through millions of dollars of client's budget for customization in the name of AI. "a scathing report from auditors at the University of Texas says the (IBM Watson) project cost MD Anderson more than $62 million and yet did not meet its goals"

So the big question is - "will the Big 5s ever create the perfect AI engine?".  That might just completely annihilate their bread & butter people based consulting model. Most of them are busy clustering their plethora of RPA (robotic process automation) engines and industry-focused analytics solutions into their flagship AI product to showcase that as their alignment to the bell curve of AI adoption. And they have baked in higher incentives for their front-line sales team to sell AI licenses so that the Trojan AI hook can then be leveraged to flow in high rate consultants."IBM Watson effectively operates as a consultancy where the company engages in high-value contracts with corporate to implement Watson technology for specific business cases"

To analyse this further let us drill down into a few of the cross-industry business challenges:

Service Operations Centres:

Contemporary CFOs of large corporates have been taking pride in driving cost transformation of their global operations through large scale outsourcing partnerships with Big 5s and other ICT firms. And whilst doing so they often perpetuated a price war amongst these outsourced partners who lifted and shifted the operations tasks to low cost location coupled with varying degrees of optimization & automation.

However, a new CFO with a taste of AI finesse will challenge the internal basics before moving the outsourcing needle - "are all these tasks really required in the 1st place?" , "How can we leverage AI to predict fault patterns and reduce the volume of trouble tickets hitting our operations centre/s?".  And then assess any need for outsourcing, if at all required. The valuable insights and prediction capabilities from an industry agnostic AI engine can transform these service operations centres into leaner just-in-time sourcing models. The traditional people based outsourcing models of Big 5s, with or without RPA and a sprinkle of AI will stand no ground against this. “A great deal of what is paid for with consulting services is data analysis and presentation...The processing power of four smart consultants with excel spreadsheets is miniscule in comparison to a single smart computer using AI running for an hour, based on continuous, non-stop machine learning” .

Regulatory Compliance: 

All companies across EU need to comply to GDPR (general data protection regulation) by May 2018 regardless of their size or industry sectors. Given the immense cost to comply with these regulations and the hefty penalties for non-compliance (4% of global topline or EURO 20 million whichever is higher), some companies have already wiped out or stopped keeping records of customer data like loyalty points, etc. The industry focused solutions for GDPR compliance will involve mix of BPO and ICT functions and will take ages to be replicated across different industries with high customisation costs.

This is a sweet spot for the traditional, people based consulting model for regulatory compliance where the Global Tier 1 FIs (financial institutions), at an average, spend almost USD 1 billion a year, with a lions share of that spend going to the trusted Big 5s charging a heavy premium for their consultants' tacit knowledge. But the FIs are still struggling to meet key regulatory deadlines -“only 36 per cent of firms who are subject to MiFID II are confident that they are on track to comply with the regulation by 3 January 2018”. And GDPR is yet another windfall opportunity with the Big 5s eyeing upto $10m per client : U.S. companies spending millions to satisfy Europe's GDPR. Whereas an industry agnostic AI solution can help operationalise real time compliance to the stringent GDPR regulations within weeks with minimal human costs.  

So it is just a matter of time, perhaps months where the true AI startups, irrespective of their size, will come face to face with the Big 5s to disproportionally disrupt their bread-and-butter people based consulting model/s.  

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Tags: AI, GDPR, compliance, network, operations, regulatory, service


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