I'll keep this short this week because I feel like I've been holding my breath for months in advance of Election Day in the U.S., and my lungs are about to explode. Maybe my brain, too. Many of you probably feel the same way.
But I do want to share some thoughts about a smart white paper from BCG that looks at the progress that has — and hasn't — been made on using artificial intelligence in business in the nearly two years since ChatGPT debuted.
The headline numbers: While 98% of companies are experimenting with AI, only 26% have moved beyond the pilot stage and are generating value. Just 4% are at what the consulting firm considers to be the forefront of implementation of generative AI.
Let's take a look at who the leaders are, where they're generating value, and how insurers stack up.
The BCG white paper opens with the enormous potential for AI:
"A financial institution is committed to achieving $1 billion in productivity improvements, in addition to enhanced risk outcomes and better client and employee experiences, by 2030. A biopharma company is chasing $1 billion in value potential (revenues and costs) by 2027. A major automaker expects to cut its cost of goods sold by up to 2% and accelerate product development by 30%."
Based on research into more than 1,000 companies worldwide, BCG found:
"Over the past three years, leaders’ revenue growth has been 50% greater than the overall average. Their total shareholder returns are 60% higher, and they gain 40% higher returns on invested capital. These companies also excel on nonfinancial factors, such as patents filed and employee satisfaction, and they are in pole position to benefit as AI platforms and tools mature."
BCG says six factors distinguish the 26% of companies it identifies as leaders:
- They focus on the core business processes as well as support functions.
- They are more ambitious. Leaders’ expectations for revenue growth from AI by 2027 are 60% higher than those of other companies, and they expect to reduce costs by almost 50% more.
- They invest strategically in a few high-priority opportunities to scale.
- They integrate AI in efforts both to lower costs and to generate revenue.
- They direct their efforts more toward people and processes than toward technology and algorithms. Leaders follow the rule of putting 10% of their resources into algorithms, 20% into technology and data, and 70% into people and processes.
- They have moved quickly to focus on GenAI.
How does the insurance industry stack up?
BCG says insurance is somewhat above-average on the firm's AI maturity curve and adds that the industry does especially well in using generative AI in core processes. On core processes, BCG ranks insurance fourth in a list of 17 industries, behind only software, media, and fintech.
BCG says insurers' biggest challenges "involve people and processes: improving staff AI literacy, prioritizing opportunities over other concerns, and establishing ROI for identified opportunities. They also wrestle with the tasks of integrating AI with existing IT systems and of increasing the accuracy and reliability of AI models."
I'd second what BCG says about insurers using AI in core processes. I've been impressed, in particular, with what I've seen concerning claims and underwriting and, to a slightly lesser extent, with agents and brokers.
I'd also say that insurers have done well on the final two of BCG's list of six characteristics of leaders. The insurance industry has focused on people and processes, rather than just on the technology, and has moved quickly.
On the other three characteristics, I'm less sanguine.
I'm not sure that insurers have been as ambitious as they could be. Even with claims, underwriting, and agents and brokers. the emphasis has been on making current processes more efficient — a worthwhile goal, to be sure, and one that can deliver quick benefits — rather than trying to reimagine processes or to plumb AI for insights on risks and customers.
I hear about fairly diffuse efforts on AI, not the "few, high-priority opportunities" that BCG saw at the leaders.
And I don't see a lot of focus on using AI to generate revenue, rather than just cutting costs.
So I'd say insurance is off to a good start on generative AI — but still has an awful lot of opportunities in front of it and could benefit from some more ambition and focus, especially on revenue opportunities.
Along those lines, we're starting an AI newsletter later this month that will highlight not just articles on ITL but from around the Web and from consulting and research firms that provide examples of innovative successes and that explain how the rest of us can emulate the leaders.
Please keep an eye out for it.
And, in the meantime, if you're eligible, please vote.
Cheers,
Paul