Generative AI and competitive advantage

Where AI makes you more competitive... and where it doesn't

CEOs are scrambling to mention Generative AI in their earnings calls.

According to this report from the IBM Institute of Business Value, 75% of CEOs believe that competitive advantage “will depend on who has the most advanced generative AI.”

Yet, this doesn’t make any sense.

AI, like most technologies, is fast becoming a commodity. In the very near future, every CEO will have access to “the most advanced generative AI”.

In other words, the “most advanced generative AI” won’t matter.

What will matter, though, is:

(1) the state of your competitive ecosystem,

(2) the factors that create competitive advantage within it,

and

(3) the extent to which AI can help attract those factors in your direction and dismantle those factors currently held by your competitors.

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Creating advantages in your competitive ecosystem

To think about competitive advantage in ecosystems, a helpful framing is to start with three sources of advantage in any competitive ecosystem.

As I explain in How to win at Generative AI:

There are three key sources of advantage in a competitive ecosystem.

Most players vying for the AI-enabled hub position will need a combination of one or more sources of such advantage.

1. Workflow advantage: Do you power the core workflow?

2. Intelligence advantage: Do you have the right to inform the core decision?

3. Relationship advantage: Do you have primacy of relationship with the key stakeholder?

Generative AI can serve as a source of competitive advantage, but not because you have access to “the most advanced generative AI”.

Whether it is an advantage or not depends on its ability to help you develop one or more of these advantages or wrest one or more of these advantages away from your competitors.

Remember, these advantages already exist within your ecosystem. They are currently held by certain players on the back of technological or regulatory or market advantages that they have and protect. If Generative AI helps you wrest that advantage away and establish it at your end OR reinforce the advantages you already have, it may well prove to be a source of competitive advantage.

The analysis below looks at three scenarios for developing competitive advantage with Generative AI:

1. Reinforcing your intelligence advantage

2. Dismantling your partner’s/competitor’s relationship advantage

3. Dismantling your partner’s/competitor’s workflow advantage

Let’s dive in… but first, a quick note on the CEO survey again.

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Short-term hype vs long-term advantage

A CEO’s primary task is capital allocation and the best CEOs excel at determining which advantages generate higher returns on capital. No efficient capital allocator actually believes that access to the most advanced AI will give them competitive advantage.

Yet, in today’s AI-hype-cycle, most CEOs are scrambling to pull capital in their direction.

Investors believe AI will drive competitive advantage, they're not yet clear which companies will benefit from it though. As a result, every company is scrambling to fit that story and attract some of those capital flows in its direction.

This is also why most capital flows are going to the ‘picks and shovels’ business of Nvidia, not because investors actually believe that it will generate cash flows to justify that price, but because the thesis is unclear on who else will.

But the short term hype-pandering notwithstanding, all CEOs are simultaneously working through understanding where advantages eventually rest.

To understand that, don’t start with AI, start with your competitive ecosystem and the factors that drive advantage within it.

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Building intelligence advantage with Gen AI

CCC Intelligent Solutions is the leading provider of auto insurance case management software, managing coordination across insurers, repairers, OEMs, claimants, and any other stakeholder in that ecosystem.

For every collision event, insurers must determine the appropriate repair facility and parts supplier, while auto repair shops must select the right parts and execute the necessary restoration work on the vehicle. CCC orchestrates this entire ecosystem.

It does all this by creating a ‘digital twin’ of the insurance case, including all the facts of the case and the evidence as well as progression of each step of the resolution.

CCC’s competitive advantage rests on the power of this ‘digital twin’ - the more decisions it can inform, the stronger its competitive positioning within the ecosystem. Essentially, CCC sits at the center of the ecosystem on account of this intelligence advantage.

CCC uses AI to improve this intelligence advantage. This includes an AI-powered repair estimating solution, called CCC Estimate – STP, which dramatically reduces the time to deliver repair estimates, improving approvals and coordination across the rest of the ecosystem.

CCC uses computer vision to analyze and assess vehicle damage photos for any make and model.

Finally, with improvements in Generative AI, CCC can convert unstructured call data to structured data that can be added to the data model.

All of the above are examples of a company using AI to strengthen its position in the ecosystem by bolstering the decision advantage that it already enjoys.

Your competitive advantage rests

• not on the ability to access the most advanced generative AI

• but on the ability to use highly commoditized AI

• to strengthen your competitive position

• through developing an intelligence advantage.

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Dismantling relationship advantages with generative AI

Another way to gain advantage in a competitive ecosystem is through dismantling entrenched relationship advantages. Players who develop deep relationship advantages - agents, resellers, etc - gain the right to charge a premium on the basis of that advantage.

Generative AI can be used to dismantle a relationship advantage with an intelligence advantage and move power in the value chain back in your direction.

Consider a classic product manufacturer - reseller relationship. The reseller typically charges a premium off the back of owning a coveted relationship with the end customer.

As I explain in AI-led growth:

In industries where relationships are critical to gaining customer trust and closing the sale (e.g. reseller relationships), AI can be used to dismantle relationship advantages.

In these ecosystems, resellers possess specialized knowledge about the product and/or the customer context based on which they continue to own the right to sell, and charge a premium for that.

A sufficiently sophisticated AI sales assistant, empowered with product knowledge (trained by the company) and customer knowledge (trained by resellers) can dismantle this relationship advantage.

This plays out in four stages:

1. Stage 1 - Assistant augmentation: The company converts its product knowledge into a ‘sales assistant’ - an AI assistant which assists resellers with the product.

2. Stage 2 - Salesforce expansion: The reseller base dramatically increases as learning curves go down for new resellers who no longer need extensive training to sell the product.

3. Stage 3 - Assistant learning: This widening base of resellers using the AI sales assistant rapidly create training data about different customer needs as they work with the assistant to address them.

4. Stage 4 - Salesforce contraction: Once sufficient customer data has been captured, the assistant is sophisticated enough to replace or augment resellers. In both cases, profits move back to the product manufacturer and away from the reseller

Note that an intelligence advantage is created here to essentially commoditize the resellers’ relationship advantage. Eventually, the product manufacturer emerges with both an intelligence advantage and a relationship advantage.

Your competitive advantage rests

• not on the ability to access the most advanced generative AI

• but on the ability to use highly commoditized AI

• to strengthen your competitive position

• through developing an intelligence advantage

• which commoditizes your competitor’s/partner’s relationship advantage.

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Dismantling workflow advantages with generative AI

A third way to gain advantage in a competitive ecosystem is through dismantling entrenched workflow advantages. Players who develop deep workflow lock-in may sit at the center of the ecosystem not because they solve important problems but merely because switching costs are too high.

If Generative AI can help commoditize workflows, it can reduce that switching costs and migrate it to another part of the ecosystem.

Again, this is achieved through building a novel intelligence advantage.

As I explain in AI-led growth:

In industries where customers are locked-in to workflows, critical decisions for the customer may sit in those workflows but may be underserved within them. By empowering customers with those decisions, AI can unlock a new sales channel.

Consider the corporate travel industry, where the travel booking problem - a decision problem - is embedded within a compliance and payments workflow. A corporate booking agency may not book optimal trips but as long as it stays compliant and streamlines approvals and reimbursements, it may continue enjoying the advantages of workflow lock-in.

This workflow advantage may be dismantled by building an intelligence advantage.

This plays out in four stages:

1. Stage 1 - Workflow augmentation: A travel booking AI assistant is embedded into the travel planning and booking workflow.

2. Stage 2 - Decision interface emerges: The AI assistant starts enabling an important and underserved decision in the workflow. Where this happens, usage may start shifting from the corporate travel booking workflow interface to the AI assistant interface. If a version of the assistant can also be provided to end users and not just the travel agent, this further ensures primacy of the decision interface.

3. Stage 3 - Assistant learning: The more travels planned and booked, the more this assistant is trained. This widening user base using the AI assistant rapidly creates data about different user needs and the assistant learns from them as it works alongside them. As the AI improves and usage shifts to the assistant, the rest of the workflow starts getting reorganised around the AI assistant.

4. Stage 4 - Decision interface dominates : As the AI assistant improves, it may absorb more of the workflow. By this time, the workflow advantage shifts to the new decision interface.

Note that an intelligence advantage is created here to essentially commoditize the incumbent’s workflow advantage. Eventually, the AI assistant emerges with both an intelligence advantage and a workflow advantage.

Your competitive advantage rests

• not on the ability to access the most advanced generative AI

• but on the ability to use highly commoditized AI

• to strengthen your competitive position

• through developing an intelligence advantage

• which commoditizes your competitor’s/partner’s workflow advantage.

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Competitive advantage beyond the hype cycle

The hype cycle of 2023-24 will end at some point.

While you’re in a hype cycle, a compelling story helps you attract capital in a market flush with capital flows.

But once we are past this hype, the true sources of competitive advantage will sustain and prevail.

The companies that eventually win will be the ones that are working today

• to leverage Generative AI

• to create new sources of intelligence advantage

• that help strengthen their position

• and commoditize partners’ positions

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Competitive advantage in ecosystems

Over the past decade, I’ve helped CEOs think through their capital allocation dilemmas - which plays will generate supernormal returns and which ones won’t. Technologies have changed but the sources of advantage haven’t.

The question that bears answering always is “How does this new technology reconfigure competitive positions in my ecosystem?”

If these are questions you’re grappling with, just hit reply and let’s discuss.