The value of artificial intelligence (AI) is often measured in terms of efficiency, such as cost savings, productivity gains, and process automation. While these are important, they are only part of the story. To scale AI technology successfully and truly realize its potential, organizations must broaden their perspective and consider a wider range of metrics, including customer experience, staff retention, and long-term strategic benefit.
Applying a value framework to AI investment
Many organizations have long adopted value frameworks to guide their investment decisions. They evaluate opportunities using a variety of key criteria, such as risk reduction or ESG impact, rather than relying solely on a simplistic cost-benefit analysis. Forward-thinking leaders understand that taking such an approach offers a long-term strategic view on investments and can give a more nuanced understanding of the potential returns.
AI opportunities should be assessed the same way.
“Why do we need a different way of looking at value just because it's AI?” a senior AI leader said, sharing his perspective at Berkeley’s panel discussion event, AI: beyond the pilot.
When you invest in an organization, typically you've got an understanding of your value framework and the things that matter – and your business KPIs – which can be very different depending on the organization. I don't think we've seen a case where we have to throw that away and start thinking of a different way of assessing value”
A senior AI leader, speaking at Berkeley's event, AI: beyond the pilot
A robust AI value assessment
Questions could include:
1.
How does this improve the customer experience?
2.
Does it reduce risk, variance or error rates?
3.
Will it improve the employee experience or reduce attrition?
4.
Does it unlock strategic capability, such as personalization or new service models?
5.
Could it support governance, compliance or audit processes more effectively?
6.
What organizational behaviours or decisions could it improve?
Customer-centric AI as a primary value driver
AI investments must first and foremost support customer experience.
“Within our contact centres, the first thing we want to do is make sure we're solving our customers’ problems. We want to reduce any friction our customers experience and that's much more important for us than efficiency. If we could reduce headcount as a result of using a voice bot, for instance, but see a drop in conversion, that wouldn’t be a positive ROI and we wouldn't take that forward as a project,” one of our panellists, Head of AI at a consumer-facing global business, explained.
This directly contradicts the common assertion that cost reduction is the primary AI value lever. Instead, when applied rigorously, value frameworks reveal that customer outcome metrics often outweigh efficiency metrics. Using AI to deliver personalised, responsive interaction can strengthen customer satisfaction and loyalty.
Ultimately, better service should drive revenue uplift. AI’s role is therefore not to cut cost at the expense of experience, but to enhance experience in ways that directly translate into commercial value.
Investing in the strategic value of AI
By definition, strategic value does not show up in simple efficiency metrics, which means organizations focused on efficiency could be missing out on AI’s biggest potential. A recurring theme across our panel was that some of AI’s most substantial value lies in new capability creation, not cost optimization.
One panel speaker, Chief Digital Officer for a multinational consumer packaged goods company, discussed AI-enabled creative generation, global brand localization, and marketing lifecycle optimization – things that were previously impossible or prohibitively slow.
“The benefits of this [gen AI] capability aren't just productivity. It’s also the quality of work that I can create. It’s the speed that I can move things ahead, whether that’s a process or decision-making. And then it’s my ability to scale across different markets, users and use cases,” she said.
One of the key interventions that we made early on was to build a kind of 'brand brain' to help guide the Gen AI creative tools that we're using to create branded assets. That's allowed us to have a 'super shoot' for a product in London and then we can localize all of those assets all across the world. We can stay on brand and use AI to test it before it even goes out so we can de-risk ourselves further.”
Chief digital officer, a multinational consumer packaged goods company
Prioritize the right AI opportunities
Our panel made one principle abundantly clear: AI is not a special case requiring a special form of evaluation.
It must be assessed through the same value frameworks that determine every other investment, looking holistically at customer benefit, organizational health, strategic advantage, risk, capability, and longterm sustainability.
When organizations apply these frameworks in the right way, AI’s value becomes broader and richer, but also more grounded in reality. Unlocking this wider picture will enable leaders to prioritize the right opportunities, focus on outcomes that matter, and build AI strategies that deliver sustainable enterprise wide impact.
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