A recent CallMiner study highlights a clear signal: in Europe, AI in CX is now a strategic growth lever, but the way it is governed will determine who will truly be able to turn this race into sustainable and defensible ROI. Omega3C and Atombit were created precisely to address this gap, helping companies connect AI, governance and the economics of customer experience, not just the technology.
What the CallMiner research says
From the perspective of the corporate board, the central message of the study “Scaling AI in European CX: Balancing speed, governance and trust in AI adoption” is that AI in CX is no longer an IT issue, but a matter of strategic execution. 99% of European organisations report being under pressure to scale AI in customer experience, but only 38% say they have a clear governance framework.
This means that most AI initiatives in CX operate in a “grey area” from a risk, compliance and accountability perspective, precisely as investors and regulators are raising the bar on responsible AI practices. For top management, the question is no longer “whether” to use AI across touchpoints, but “under what conditions”, with which success metrics and with which control mechanisms embedded in the operating model.
The risk of a “velocity-first” adoption
The research shows that 59% of companies are scaling AI in CX very quickly, but only 39% believe that compliance is actually keeping pace. This asymmetry creates three risks that are typically underestimated at executive level:
- Regulatory risk: in a context shaped by GDPR and the AI Act, demonstrating ex post compliance of AI systems that interact with customers is complex if structured governance has not been designed from the outset.
- Reputational risk: without adequate human oversight, explainability and safeguards for vulnerable users, AI can generate isolated incidents that damage trust in the brand disproportionately compared with the individual incident.
- Economic risk: investing in fragmented AI initiatives, without a clear ROI model and without the ability to measure the impact on retention, share of wallet and cost-to-serve, leads to a portfolio of projects that is difficult to defend during budget reviews.
La stessa ricerca mostra che solo una minoranza ha già implementato in modo maturo audit regolari, capacità di spiegare le decisioni AI e controlli specifici per clienti vulnerabili. Per un C‑level, questo è un chiaro “execution gap”: l’AI entra a pieno titolo nel core business prima che i processi di risk management e di performance management siano adeguate.
Trust, data and sales: where value is created
For business leaders, the real issue is not the individual technology, but AI’s ability to influence the variables that drive the P&L. CallMiner highlights three key areas:
- Trust as a driver of adoption: more than 7 out of 10 organisations say that employee trust and customers’ willingness to accept AI-driven actions are determining factors for scaling. AI perceived as a “black box” slows internal adoption more than it accelerates it.
- Data as an underutilised asset: despite increased investment, many companies struggle to turn customer interactions into actionable insights, with difficulties in connecting CX data to cross-functional decisions.
- Third parties as an accelerator (and risk): 51% of organisations say they rely primarily on third-party AI software, enabling faster adoption but also requiring careful assessment of vendor risk and the ability to orchestrate different solutions.
For a CEO or CFO, the question becomes: how can these elements be turned into measurable growth levers (revenue, margins, customer lifetime value) and into a credible story for investors and stakeholders around AI that is “responsible but competitive”?
How Omega3C and Atombit support corporate boards
Atombit is now a pan-European leader in Experience Intelligence, bringing together customer and employee experience, data analytics and AI with a clear focus on ROI. The acquisition of Omega3C, a company with more than 20 years of experience and over 100 CX and EX transformation projects across Europe, has further strengthened this capability, integrating strategic consulting and operational execution.
For a C-level executive, this translates into the opportunity to have a partner that:
- Connects strategy and operations: starting from growth, profitability and positioning objectives, it designs AI adoption roadmaps for CX that clearly define where AI needs to impact the P&L (revenue, costs, risk) and how to measure it.
- Builds “AI governance by design”: integrates responsible AI principles, GDPR and AI Act requirements, audit processes, explainability and vulnerable-user management into service models, rather than treating them as an additional layer downstream.
- Orchestrates technology and partners: helps select, integrate and govern conversation analytics platforms such as CallMiner and other AI and contact centre solutions, avoiding overlaps and wasted investment.
- Brings evidence, not just reports: thanks to established data analytics and experience measurement practices, it enables companies to demonstrate – with numbers – the impact of AI on churn, cross-sell, NPS, CSAT and cost-to-serve, supporting subsequent investment decisions.
In summary, Omega3C/Atombit offer corporate boards a way to turn the urgency to “do AI” into a transformation programme driven by business cases, shared KPIs and a level of governance aligned with the expectations of European regulators.
If you are defining how to accelerate AI adoption across contact centres and digital journeys, but questions are emerging around risks, control and returns, we propose a confidential meeting with an Omega3C/Atombit expert to:
- Map the current state of AI initiatives in CX, from the perspective of risk, governance and economic impact.
- Identify 2-3 priority use cases capable of generating value in the short term, in line with growth and efficiency objectives.
- Design an “AI in CX” roadmap that can be discussed and approved at board level, with clear success metrics and an integrated governance framework.
- Implement and scale in a controlled way: support the organisation in execution, moving from pilot projects to industrialised deployments, with change management plans, targeted team training and a continuous monitoring model that keeps risks, performance and economic returns under control.
In this way, AI in CX becomes an integral part of the operating model and the P&L, rather than an experimental initiative destined to fade away at the first challenge.
Book a meeting with one of our experts!