Game Changing AI Use Cases for Go-To-Market
Last week I attended an insightful Gartner webinar focused on how to assess and prioritize valuable GenAI business use cases.
Whilst there is a lot of buzz around AI, and plenty of people are enjoying playing with ChatGPT, senior executives are urgently getting serious about how AI can transform the way their business looks and operates in the coming years.
CEOs are focused on AI
Let’s just level set - CEOs are focused on AI. When they are discussing with their peers they recognise that this is one of the biggest shifts in how their business runs since the arrival of the internet, or even electricity.
This is not an IT initiative, or a finance initiative - it is a company existence initiative.
The CEOs that get this wrong, or wait too long, risk eroding or entirely destroying shareholder value and being out of a job in just a few quarters’ time.
Business strategy classes talk about the demise of Blockbuster or Kodak as a lesson from the past.
Every company today is a potential Blockbuster or Kodak of tomorrow if they get this wrong.
Identify your Enterprise AI Ambition
It is too easy for companies to fall into the trap of playing with the technology and spinning up proof’s of concept based on ideas they have seen elsewhere - “Let’s create a new chat bot for our customers”
In a recent podcast Jennifer Tejada, CEO of PagerDuty shared that the Enterprise CEOs she speaks with are focused on three goals with AI:
Increasing or protecting revenues
Growing margins (by reducing costs)
Minimising risks (whether financial, security, people, legal or any other risk)
Gartner provide this useful AI Opportunity Radar to guide your team’s thinking about where AI can impact these three high level goals on your business..
The radar has two axes:
The vertical axis goes from external usecases (for your customers, partners and suppliers) to internal use cases, for your internal people, processes and systems.
The horizontal axis goes from everyday AI (improving a high-volume repetitive use case like holiday requests or customer support tickets) to game-changing AI (such as new business models and new product categories)
The concentric circles signify the feasibility of a particular idea, based on the available technology, the internal resources to deliver it, and the external capacity to accept and adopt it.
Jennifer goes on to say that some of the most valuable usecases are coming from non-IT and non-AI literate teams. They are coming from the people closest to the business process and the customer. They know what is broken and they know where the opportunity sits.
Broadly if you draw a line from the top left down to the bottom right, on the left hand side of the line your use cases focus on improving your margin by stripping out costs - think of that auto-expense approver or customer service chatbot - can we operate our business with fewer people?
On the right hand side of the line your use cases focus on delivering incremental revenue through new external facing product or service offerings, or improved core capabilities that allow you to charge a premium (think of Amazon’s vertically integrated stack)
AI is not a bolt on to the strategy, it is the strategy
Gartner goes on to reiterate why AI is the company strategy, not a bolt on to the company strategy.
If AI use cases are the path to higher revenues, protecting or growing margins, or minimising risk to the business, then this is a top level strategy, not a quirky side project.
You can look at your AI strategy through these two dimensions:
Is what you are considering game-changing,
and is it fundamentally different to what you do today?
It is easy for your AI initiatives to only tackle one of these - an AI enhancement to your current product or services (that support chat bot), or a new AI tool that is disconnected to your current products, but doesn’t change your business model or revenue streams (think of this like dipping your toe in the AI pool).
The top right is where we have true AI innovation - where instead of trying to incrementally improve what we have today, we imagine a new world.
This is where we ask “What if” and imagine a company with a completely different set of strategic choices of where to play and how to win.
What if - a factory existed that had zero people inside it?
What if - new medicines were developed without human involvement?
What if - our products were immediately available globally and in local language?
Prioritise high value AI use cases
Gartner describes three categories of AI use cases,
Defend - task-specific improvement, competitive parity
Extend - an existing process for differentiation
Upend - to create new products, markets, core processes
It is the upending use cases that senior executives must be focused on - as this is where the domain innovation will come from that allows you to dominate your market of the future.
There is only so much cost and time you can strip out of an expense approval policy, but the upside to a new commercial model is unlimited.
Assess your options
Gartner provides a framework to help you determine your priorities:
Have your teams list out business use cases for AI - these could be external, internal, game changing or every day.
Then score each of these usecases against the value and feasibility of delivery.
Value:
Increase revenue - new commercial models, new revenue streams, price premium
Increase efficiency - lower costs, improve margins, speed up processes
Manage risk - lower risks, mitigate impact of risks - commercial, security, legal, people
Non-financial value - brand, strategic partnerships, acquisitions
Feasibility
Technical feasibility - does the technology exist, do we have the technology available to us?
Internal readiness - do we have the people available, are our people open to adopting new ways of working or launching new offerings to customers?
External readiness - are our customers, partners and suppliers ready to work with us in this new way?
Having your team score each of your potential use cases across these dimensions allows you to present these on what Gartner calls a GenAI Use Case Prism, like this one for banking.
The use cases near the top are both high value and high feasibility - your priority.
AI use cases for Go-To-Market leaders
To conclude, let’s bring this back to Go-To-Market teams, and revenue leaders - Chief Revenue Officer, Chief Commercial Officers - the senior exec responsible for revenue.
When you now consider the topic of AI you’ll see that many of the revenue related use cases are internal every day use cases.
Recording and analysing sales calls
Crafting emails
Automating customer success and support processes
can we do more with less
I’d encourage you to think further about your value proposition for your customers, your suppliers and your partners and how you can launch game-changing external use cases.
What are your customers, suppliers and partners’ desired gains and what prevents them from achieving those gains?
What if you could deliver those gains in a totally new way, through new channels, in new countries, in different categories?
By getting back to your customers needs and designing new products and services for this new world, you’ll be in a much better position to embrace the opportunity of new revenue sources, whilst your competitors are focused on defensive cost control measures.
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