How Agentic AI Benefits Customer Contact 2025-2030
Article by – Martin Hill-Wilson, Brainfood Consulting
The Importance of Foundation Understanding
Part of Brainfood Training’s mission is expanding foundation understanding of AI to enrich the debate and improve the decisions made by organisations on how AI is used.
We provide online learning which helps ‘customer engaging’ teams gain confidence and find their own voice on AI. We also deliver a live workshop version which offers the additional buzz of an engaged roomful of people exploring new ideas together. Energised brains learn faster.
Feedback tells us the decision to focus on foundation understanding remains the right one. Organisations still need it and the benefits it brings. Finding our own words and mental models facilitates critical thought. This leads to better decisions and outcomes. Therefore expanding foundation understanding helps us become better at our jobs.
Developing a more informed perspective also qualifies us to influence a broader debate. One we are all implicated in.
There is always going to be contrasting choices in the type of AI powered world we want to live in. There is plenty of vested interest at stake. But are you tuned into the way these choices are developing? More importantly, which one are you going to back? The ability to lead and influence this crucial debate starts with investing in a solid foundation and grasp of what going on.
Put it this way. The AI first organisation you are part of in 2030 is being shaped by the discussions and decisions being made today. We all need to show up.
So What’s Happening?
The news is that Generative AI has now gained the ability to act. Welcome to the world of Agentic AI which gets its name from the idea of ‘agency’ – having the power and capacity to make choices and decisions, and to act on them.
What are the implications?
There are many. But one of the key ones is that some now believe this changes the debate around whether AI augments or replaces roles. Whatever the truth, there are many powerful voices starting to advocate the latter.
That said, what ends up happening over the next few years is likely to be more nuanced than any of the options coming out of polarising online debate. Instead, each of us needs a deep dive into the evidence for and against to form our own opinion. Hopefully the deep dives Brainfood Training makes into Agentic AI will contribute,
BTW there’s no need to feel panicked.
To date, you have not missed much. 2025 is still the dawn of Agentic AI. Especially for non technical minds. If you are just tuning in, we are at the stage of being sold a vision.
That means we need to be alert. So here’s what to focus on.
Have we enough foundation understanding to recognise the vested interests that are going to dominate our attention, influence what we believe we now want, then nudge us into behaviours we assume will make us happier/more successful etc.
Déjà vu?
The algorithms driving social media were once celebrated for bringing people together. Now they are criticised for hijacking our quality of life. Even so, resetting the role and value of social media has proved painfully slow in the face of vested interest. Despite growing evidence of the damage and a groundswell desire for change.
If once again we are too slow off the mark, the shadow that Agentic AI might cast over the next five years could be even darker. Especially for those lacking enough foundation understanding to discriminate. This could result in them passively accepting the ‘gift’ of having an AI companion able to think and act on their behalf. From dawn to dusk. From cradle to grave.
Of course, you and I won’t fall for any of that. Or will we?
This stage in the Agentic AI story has yet to arrive. But it’s being planned and grows from the seeds of what’s being currently planted today – mini steps of autonomous decision making.
The Agentic AI Series
This is the first in a series of articles exploring the impact and challenges of Agentic AI. It’s your foundation understanding module. Some topics have already been hinted at. So what else is going to be covered in the series?
We’ll start by exploring the evolutionary path from LLMs as passive text generators to autonomous decision-making systems. Quite an evolutionary leap when you think about it! All explained of course in non technical language.
Then you’ll get a chance to develop your own mental model of how Agentic AI works – the core capabilities in an Agentic AI solution. We’ll use that to trace the differences between what a simple and complex deployment looks like. This will give us our first glimpse of what the Agentic AI North Star looks like.
Once that’s understood, we can then ask the question if the vision of Agentic AI is ready to be operationalised.
There are two parts to that answer. One is technical, the other is operational.
Agentic AI as an overhyped marketing message wants you to believe that all the bits in the box lets you to build the picture stuck on the front of the box. Ten year old buyers might be disappointed when they discover that’s a classic marketing trick. We shouldn’t be.
It’s still an overlooked fact that the grandest versions of agentic AI (the one on the front of the box) require yet-to-be-launched, more advanced components. However, the starter version and associated ROI are now ready to go.
Also note that while terminology is still quite fluid, you are just as likely to hear the language of ‘AI agents’. Maybe this becomes the default since it does sound more down to earth and less operatic that ‘Agentic AI’.
So what can AI agents do? And what does the timeline of realistic use cases look like as these functional gaps are being plugged? There’s a trailer in the final section of this article hinting at how Agentic AI will impact customer contact over the coming years.
So what’s the other part of the answer on whether all this is ready to be operationalised?
As might be expected, 99% of current market focus is on what powers the technology rather than what powers the value extraction and the right focus/process for doing that.
Gartner’s hype cycle tells us market attention only shifts after a technology enters its ‘trough of disillusionment’ which is the phase that Generative AI currently finds itself in. As expected, Agentic AI has replaced it. Now perched at the top of the hype cycle.
Of course, a bumpy reset is not inevitable for those with enough foundation understanding to set the right expectations within a vision of long term strategic intent.
If that’s you, then make sure you join us for the last part of the series. We going to explore where the yellow brick road of Agentic AI eventually leads and consider what the future of work will look like through that lens.
And along that path, we’ll highlight the change management challenges and consider how the world of customer contact is going to evolve as a result.
Previewing The Impact of Agentic AI on Customer Contact
If you can’t wait that long, here’s that promised preview of what Agentic AI is due to deliver as far as customer contact is concerned over the next five years. Engaging with the series will provide the context and explanation for how this capability works and how we will reach it. But right now simply enjoy the prospect of how customer contact could transform.
BTW – you may have operationalised some of this capability already or be getting ready to since this is an evolution of existing AI powered capabilities.
Intelligent Virtual Agents for Routine Queries
- Automate high-volume, repetitive questions (order status, FAQs, account info).
- Use persistent memory for personalised greetings and context continuity across sessions.
AI-Powered Agent Assist
- Real-time knowledge surfacing, suggested responses, and next-best-actions for human advisors.
- Summarisation and sentiment analysis during live interactions.
Omnichannel Orchestration
- Unified context and handoff across chat, email, voice, and social channels.
- Memory-enabled agents recall previous interactions regardless of channel.
Proactive Customer Engagement
- Agents initiate outreach based on behavioural triggers, lifecycle events, or predicted needs.
- Dynamic, personalised recommendations using long-term customer memory.
Self-Evolving Knowledge Bases
- AI agents autonomously update FAQs and support documentation by monitoring new issues and solutions.
- Automated content curation and tagging to keep resources current.
Real-Time Feedback Loops
- Agents collect, analyse, and act on customer feedback, adapting scripts and workflows without human intervention.
Autonomous Case Resolution
- Agents handle complex, multi-step service requests (returns, escalations, troubleshooting) end-to-end, including cross-system actions.
- Error recovery and self-correction mechanisms reduce escalation rates.
Multi-Agent Task Orchestration
- Specialised agents collaborate to resolve cases, combining expertise in billing, technical support, and logistics.
- Dynamic workflow adaptation based on real-time context and customer history.
Predictive Issue Prevention
- Agents identify patterns of emerging problems and proactively reach out to affected customers with solutions before issues escalate.
Self-Evolving Service Workflows
- AI agents autonomously redesign and optimise customer service processes based on evolving data, outcomes, and business goals.
- Continuous A/B testing and workflow refinement without manual reconfiguration.
End-to-End Autonomous Customer Journeys
- Agents manage entire customer journeys, from onboarding to retention, adapting touchpoints and interventions in real time.
- Integration with business systems (CRM, ERP) for holistic decision-making.
Strategic Decision Intelligence
- AI-driven insights inform CX strategy, resource allocation, and product/service improvements.
- Agents simulate “what-if” scenarios and recommend strategic changes based on aggregated customer data and business objectives.
As you will have noticed the list progressed from ‘simple’ to ‘complex’. From ‘here and now’ to five years in the future. The list offers a ‘wireframe’ North Star to imagine how customer contact is designed and functions by the end of the decade. More than enough to spark all sorts of questions.
Next Actions
Hopefully this scene setting has whetted your appetite to learn more. The rest of the series will be published here as well.
As ever, thanks for your attention and time.
