AI is disrupting every industry and every function within those industries. In this post we’re going to look specifically at how AI is transforming the role of the Chief Revenue Officer.

A CRO is not a VP of Sales or Head of Sales rebranded - a true CRO has full responsibility for the way a company makes money - covering all of their revenue sources, the channels, the pricing and monetisation strategies, the customer segments and markets the company plays in, as well as exploring future acquisitions.

Even though we live in a fast paced world where senior execs are measured in terms of quarters, as a CRO you should be planning in terms of years, ensuring your company has the right revenue architecture and capabilities to win in the future - and this is where your AI strategy is key.

The way your revenue team is structured and operates in the future will be very different to how it is today - and it is your responsibility to take your business there proactively rather than allowing it to creep up on you.

The Gartner AI Opportunity Radar

To help you think through the opportunities in front of you I’m using Gartner’s AI Opportunity Radar.

It is a simple template that allows you to assess your AI opportunities across three dimensions:

External use cases (for customers, partners and suppliers) to internal use cases (for your own teams and processes)
Everyday AI (for existing repetitive tasks) to game-changing AI (that will transform your company and industry)
The third dimension are the concentric circles which look at the feasibility of an idea with the inner circles having the technical possibility, the internal support and external stakeholder readiness, to the outer circles where the technology is not ready yet, internal teams are not supporting and external stakeholders are not ready for this new way of working.

AI opportunities for revenue leaders

I’ve mapped out around 40 potential use cases for AI in the revenue function, and I’ll walk you through the four main categories before suggesting where you might want to apply your focus.

Back office (everyday AI for internal teams)

When we think about AI these are often the first use cases that come to mind, because we know the current processes intimately and we can understand how automating them could free up our time.

Many of these use cases are already in play - automated revenue forecasting with tools like Clari. Opportunity qualification with Gong. Employee productivity tools with ChatGPT.

In the outer rings we see opportunities to enhance contract negotiation, assigning territories and planning your sales workforce appropriately.

The business value of these tools is primarily doing more with less - removing inefficiency from the sales process, reducing your COGS and improving your operating margin.

The key to realising these benefits is having a plan for what you will do with that saving and measuring it.

If you plan to save 10% of your sellers’ time - will you reduce your sales expense by cutting headcount, or will you reassign that time to more revenue generating activities with an increase in attainment?

Without a plan, that 10% will disappear with no measurable benefit.

Front office (everyday AI for external stakeholders)

The second most common use case I hear is a customer chatbot on the website.

In February Klarna (the pay later firm) announced their OpenAI powered support agent was now handling two thirds of all customer requests.

This gets a lot of senior executives excited - imagine the reduction in headcount, office space, training and enablement. Not to mention that customers are getting to the right answer faster which is all they care about.

In the AI Opportunity Radar I encourage you to think beyond this use case and to consider all the different external stakeholders and how you can better support them.

Prospects need different information from customers
Large customers need different information from small customers
Legal personas need different information from financial personas
Partners need different information from customers
Suppliers need different information from partners or customers

Completing a buyer journey map is a good starting point here. Instead of starting with your AI ideas, start with what each external stakeholder is trying to achieve at each step of their process, and work back to how you could deliver a higher value to them using AI platforms.

Today we’re already seeing digital sales rooms like Trumpet and outbound messaging tools like Lavender improve the quality of external content.

We’ll see the evolution of the digital CSM that is deeply integrated with a customer’s product usage.

Automated creation and updating of your ICP, your buyer personas and the value proposition for each of them will move us beyond tired decks and documents.

These usecases are valuable - in many cases like the Digital CSM or Digital SDR they enable efficiencies by stripping out the human cost, but they also introduce new revenue opportunities that didn’t exist before - consider that you can now prospect and support customers in languages and timezones that you don’t have humans for.

Core capabilities (game-changing AI for internal people and processes)

Now we’re switching to the right hand side of the chart - game-changing AI.

So far the opportunities have been ‘nice to have’ efficiency boosters, more about stripping cost than changing the way the business runs.

When we think about core capabilities we are thinking about the guts of our company - and this will vary depending on the industry you are in - a tech company creating software has very different operations to a manufacturer making shampoo.

Consider your key processes:

Bringing an idea to market
Procuring a product to paying for it
Distributing your product to your customers
Building or leasing facilities
Launching in a new geography
Assessing and executing acquisitions

Each of these processes make up the core capabilities of your business and allow you to compete with others in your segment are an opportunity to innovate.

Let’s take Amazon as a well-known example.

Their vertically integrated stack aligns a global network of sellers, an easy to use “one click” website, next day delivery, and a network of cabinets with “no questions asked” returns. Together these have customers asking “why wouldn’t I use them” instead of “why should I?”

As a CRO these core capabilities are at the heart of your overall proposition in the future - considering new product development, industry use cases, partner programs, and for those that have it - managing your supply chains and facilities with digital twins.

This moves on from efficiency gains to core business strategy - where are you going to play and how are you going to win in the future?

Product/Services (game-changing AI for external stakeholders)

We come to our final quadrant, where we look at ways that you can use AI to launch new and improved products and services for your prospects, customers, partners and suppliers.

This is about growing or protecting your revenues - totally aligned with your long term incentives as a CRO.

Let’s start with existing customers - as we know, it is far cheaper to win a dollar from an existing customer than it is for a new logo.

Already today we see tools like Gainsight providing early warning of churn risks and customer health scores.

Beyond this consider the propensity for a customer to renew, upsell or expand (cross-sell). How can you use product usage data combined with other data sources to navigate your teams around larger organisations - uncovering new use cases and expanding your value.

Tools like Gong allow you to capture customer sentiment and opportunities at scale from across all your customer support and customer success interactions. Too much revenue is left on the table because growing the account is not the direct responsibility of the person speaking with the customer.

Can you launch dynamic pricing models that capture more value through the life of an agreement?

In terms of new customers, can you use the data from your existing customers to better evidence your value proposition?

Can you automatically connect prospects with existing partners and drive referrals and resale opportunities?

Can you develop and maintain clearer positioning content that helps your customers understand when and why they would need your product?

You need an AI owner and an AI plan

Through this article we’ve seen that there are many opportunities for the revenue function to embrace and benefit from AI - but it needs a plan. Without it you risk reactively bolting on bits of AI that may drive some efficiencies, but leave you trailing in two years time.

I’ll be walking through a recommended process and how you staff your team for this challenge in a future post - but for now do two things.

Create a cross-functional group from across your revenue teams to assess the opportunities specific to your scenario
Run a workshop session where you map out all the possible ideas on a canvas like the Gartner AI Opportunity Radar.

Now you have a starting point to work from.

If you want help facilitating this process - I help CROs with exactly this.

Get started

Whenever you are ready, there are three ways that I can help you accelerate your revenue.

Buyer Enablement Assessment - Answer nine questions in five minutes and receive your free personalised report to help you SDRs and AEs generate pipeline.
Revenue 360 Assessments - inspire and lead your revenue teams with revenue specific 360 reports designed for marketing, sales and customer success teams.
Buyer Enablement Platform - We’ll design, build and manage your buyer enablement platform on your behalf - generating quality pipeline in under 90 days.

AI Opportunities for Chief Revenue Officers