Each technological revolution redistributes the cards. The 2000s saw the emergence of e-commerce: Amazon, Zalando and Cdiscount built their domination on the speed of their investments.
The 2010s were all about mobile, and few brands have caught up after being late in launching their application. More recently, the cloud has opened a new era of flexibility and performance, widening a lasting gap between pioneers and followers.
We are experiencing the same phenomenon today with Agentic AI, these intelligent agents capable of reasoning, learning and executing complex tasks independently. It is no longer a distant horizon: it is already an operational reality. And, as with every technological turning point, the question arises acutely: should we invest now, or wait? History teaches us: those who wait are overtaken.
The emergence of a new generation of AI
Since the emergence of chatbots, businesses have become familiar with conversational interfaces. Then generative artificial intelligence opened the way to richer uses, capable of producing text, code or visuals. The next step, Agentic AI, takes a decisive step forward: it is no longer just a matter of generating content but of acting, making decisions and orchestrating several tasks independently.
Concretely, an AI agent can qualify a customer request, extract relevant information from an internal system, write a personalized response, trigger an action and transmit a file to a human advisor if necessary. It becomes a full-fledged player in the value chain, and no longer a simple support tool.
This development is not marginal. According to a Google Cloud study conducted in 2025, 52% of executives say their organization has already deployed AI agents in production. Among them, almost 40% use more than ten different agents. In other words, we are no longer in isolated experimentation but in a wave of massive adoption.
Benefits already measured
Initial feedback shows that these agents deliver tangible results. The PwC “AI Agent Survey” (2025) reveals that 66% of companies that use AI agents see an increase in productivity. More than half report significant cost savings, faster decision-making and improved customer experience.
These figures reflect a concrete competitive advantage. By taking care of repetitive tasks such as qualification, routing or simple responses, the AI agent frees up time for employees, who can devote themselves to complex, high-value interactions. By automating part of the customer flow, companies reduce their operational costs while improving their Net Promoter Score and reducing churn; in some cases, the return on investment is measured in a few months. An AI agent can also detect a need, offer a relevant recommendation and transfer the request to the right salesperson at the right time, becoming a direct facilitator of additional revenue.
The impacts concern the entire organization. According to a PagerDuty survey conducted in 2025, IT is the first area to benefit from AI agents (69%), followed by customer service (41%), finance (39%), sales (37%) and marketing (36%). Human resources (32%) and legal services (30%) also benefit from significant gains. In some countries like the UK, expectations are even higher than average, with 77% of executives convinced that IT will reap major benefits.
These benefits are already being verified on the ground. Wyndham Hotels & Resorts has deployed AI agents to streamline its guest and operational services, improving both guest satisfaction and internal efficiency. In banking, several players are testing agents capable of automatically qualifying requests and strengthening compliance. In retail, brands rely on these agents to personalize purchasing journeys and speed up order processing.
The cost of inaction
Conversely, organizations that do not hire an AI agent take a double risk. First, that of maintaining structurally higher costs, due to lack of automation. Then, that of offering a less fluid customer experience than their competitors, who will offer more speed, personalization and availability.
In a context where comparison is immediate – it only takes a few seconds to change supplier or express dissatisfaction on social networks – this performance gap can quickly translate into a loss of market share. Even more serious: it becomes very difficult to catch up once new standards are installed.
As with e-commerce or the cloud, timing is decisive. Adopting too early can expose you to costly experimentation. But adopting too late means running behind already established leaders. The right time is now: Agentic AI has reached sufficient maturity to deliver a concrete business impact, measured and validated by the first deployments.
A transformation beyond technology
The adoption of Agentic AI is not limited to the integration of a new tool. It involves a profound reorganization. Data quality becomes an essential prerequisite, because an AI agent is only as efficient as the information it has; preparing, cleaning and structuring data is therefore essential. Training and improving the skills of employees is also key so that they can work with these agents, supervise their actions and exploit the new opportunities that result from them. Finally, continuous supervision is necessary to guarantee quality, transparency and compliance with ethical rules. This transformation is not a secondary option: it conditions the success of the deployment and acceptance by both teams and customers.
Agentic AI is not a fashion, it is a structural break. Studies by PwC and Google Cloud demonstrate this: half of companies have already taken the plunge, and the majority are reaping measurable benefits.
In this context, inaction is a risky bet. Waiting means giving up immediate gains in productivity and customer satisfaction. It also means letting your competitors establish a competitive advantage that is difficult to catch up with.
Agentic AI is a new frontier in performance, ROI and growth. Those who take this step today will gain a lasting head start. Those who hesitate will, once again, watch as their competitors pass them by.
Notes and sources
· Survey PagerDuty 2025
· PwC AI Agents Survey (2025)
· McKinsey – “Empowering advanced industries with agentic AI”
· MarketsandMarkets (2025)
· Google Cloud Study (2025)
