When 2025 began, the anticipated term of the year was generative AI (artificial intelligence), a term that has been gaining momentum for a few years—and then somewhere in the first or second quarter of 2025 agentic AI smacked us in the face.
If you have been following along here at Connected World and The Peggy Smedley Show, then you know we have been covering agentic AI in depth, looking at the impact on industries like manufacturing, supply chain, construction, transportation, energy, smart cities, and more. It certainly has been the talk of the second half of 2025 for many industries.
Simply, agentic AI builds on previous models by enabling AI systems to act autonomously to complete tasks. Agentic AI is a system that can observe, plan, and act to complete tasks or entire workflows autonomously, with human oversight. This can help in many ways in many different industries.
For today’s blog, let’s look at the impact of agentic AI on the customer experience. Both customers and businesses will engage with the technology to automate interactions.
Agentic Growth Ahead
To start, we see a new study from Juniper Research found the number of customer interactions automated by AI agents will grow from 3.3 billion interactions in 2025 to more than 34 billion by 2027. This is a surge of roughly 1,000% in the next two years.
Why will we see such speedy growth? Enterprises galore will adopt the technology to support customer interactions in customer service, marketing, and sales, just to name a few.
Adding fuel to the fire, Gartner suggests agentic AI will autonomously resolve 80% of common customer service issues without human intervention by 2029, which could lead to a 30% reduction in operational costs. That’s a pretty bold claim, when you think about it.
The analysts are certainly placing their bets on agentic AI, but the more important question is what will this ultimately look like for businesses? Perhaps an even bigger question is the existential concerns that exist and that seem to be widespread. But a recent survey shows 77% are concerned AI just might pose a threat to humanity, including 39% who are very concerned, according to YouGov. Interestingly, in sectors like finance, healthcare, and automotive, trust dips considerably.
How to Prepare
But let’s get back to the topic at hand, which is agentic AI in customer service and what will it actually look like? We can assume it will leverage customer data to make recommendations and provide a higher level of service. But the opportunities run so much deeper than this.
Boston Consulting Group suggests there are four stages of customer service optimization where AI can provide high impact including:
- Pre-empt: Leverage AI to prevent issues and requests from arising.
- Self-heal: Use AI to proactively address issues and requests before the customer notices them.
- Self-help: Equip customers with AI-based tools and information to self-solve their issues and requests.
- Support response: Enable service agents to efficiently resolve customer issues and requests.
Most AI deployments today begin at the support response end, reducing average handling time, guiding agents with next best action suggestions, or summarizing calls. Although agentic AI could potentially increase value across all four stages, with the highest value in the pre-empting issues and self-healing.
Still, Boston Consulting Group suggests the biggest challenges we face are the change management required, the current fragmented technology ecosystem, and the need for orchestration across platforms, systems, and vendors. This is no easy feat.
As such, Juniper believes enterprises will prefer platforms that minimize upfront investment and development timescales. With so much data already existing within systems, agents can leverage data that already exists. However, for this to come to fruition, vendors must provide prebuilt integrations across enterprise systems to support businesses as they scale.
Here’s the hard reality. Boston Consulting Group suggests only 28% of companies have unlocked measurable business value from generative AI in customer service. Then, how can we expect to grow and scale agentic AI at the rate anticipated by the analysts? That is certainly a question to ponder.
I’d say companies need to focus on the need and how agentic AI can meet that specific need. As we always say, technology for technology’s sake helps no one. Businesses must focus on the business case first and foremost. What are your thoughts for customer service?
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