The OCX Observatory data shows that the main barriers are not technical, but strategic and operational. The 33% of companies indicates the lack of a clear AI strategy as the primary obstacle to structural adoption. Next in line are difficulties integrating with existing systems (32%), which makes it difficult to connect AI to CRM, marketing, and customer service platforms.<\/p>\n
Other significant obstacles include unmapped or non-standardized internal processes (25%) and cost or budget constraints (24%). In short, the technology is available, but the organizational and process architecture to support it is often lacking. Also significant is the still marginal weight of issues such as ethics, risk management, model hallucinations, or customer acceptance.<\/p>\n
These aspects, currently secondary in the Italian sample, are instead central in the international debate and in emerging regulations such as the European AI Act (official EU website<\/a>). It is reasonable to expect that, as AI enters more critical and customer-facing contexts, Italian companies will also have to systematically address these dimensions.<\/p>\n The research highlights a key point: AI is not the starting point for omnichannel transformation, but rather an accelerator that puts pressure on existing foundations. Where direction, integration, and a unified vision are lacking, the introduction of AI can amplify inefficiencies and information silos, rather than generating value for the customer experience.<\/p>\n To transform the\u2019AI omnichannel<\/strong> A true Customer Experience enabler requires certain enabling conditions. The OCX research highlights four interconnected pillars that distinguish more mature companies from those still in the experimental phase.<\/p>\n The first element is strategy. Without a clear direction for AI, projects remain isolated and difficult to scale. Initiatives that begin as local experiments, if not incorporated into a shared roadmap, risk producing only "islands of innovation" poorly aligned with overall customer experience objectives.<\/p>\n An effective omnichannel AI strategy must define priorities, use cases, success metrics, and expected impacts along the customer journey. Only then can AI have a structural impact on processes, service models, and business outcomes, rather than remaining an afterthought.<\/p>\n The second factor concerns governance. The research shows a still fragmented market: only about a quarter of companies coordinate AI projects through a central management team, while nearly half grant broad autonomy to individual business units.<\/p>\n This autonomy fosters experimentation, but exposes the risk of duplication, information silos, and non-scalable solutions. In more advanced clusters, however, centralized governance of omnichannel AI emerges, capable of aligning priorities, budgets, responsibilities, and impacts, especially on the OCX and customer journey fronts.<\/p>\n The third element is skills. AI adoption is progressing faster than the ability to develop appropriate skills. Only 11% of companies report having specialized and advanced skills, while the majority rank at intermediate or low levels.<\/p>\n Even among the most mature organizations, a significant gap remains, making it necessary to build an ecosystem of technology and consulting partners. In this context, it is useful to combine internal expertise, centers of excellence, technology vendors, and cloud platforms specialized in AI and data, such as the machine learning services offered by major hyperscalers (Google Cloud AI<\/a>, Microsoft Azure AI<\/a>).<\/p>\n Finally, change management remains a critical cross-functional factor. Internal training, pilot projects, dedicated task forces, and front-line involvement are the most common actions to support people and processes in AI adoption.<\/p>\n The centrality of the human factor is recognized regardless of the OCX maturity level. Without a structured support path, even the most technologically advanced initiatives struggle to generate value. Omnichannel AI requires hybrid models, in which AI empowers people, supports decisions, and reduces complexity, without completely replacing human intervention.<\/p>\n The OCX Observatory's analysis reveals a clear gap between the potential of AI and the way it is currently used in Italian companies. In most cases, AI is used as a support tool or local automation, without redesigning customer experience models.<\/p>\n<\/p>\n 33% of companies use AI for empowerment activities, supporting people in existing operations. 30% use it as a tactical addition to automate individual operational steps, often in specific channels or touchpoints. A significant portion, equal to 16%, declares that it has not generated any significant changes in processes.<\/p>\n Only a minority uses AI as a lever for partial or strategic process redesign, with overall percentages of just over a fifth of the sample. This is where the real quantum leap lies: "Champion" companies are able to integrate omnichannel AI into the organization's overall operating logic, rethinking flows, responsibilities, and interaction methods throughout the entire customer journey.<\/p>\n However, the research warns of a concrete risk: the complexity trap. Introducing AI solutions in a fragmented manner, without building the basics of customer experience and a coherent data strategy, can actually worsen the customer experience. Silos increase, inconsistent touchpoints multiply, and it becomes more difficult to redesign end-to-end processes for omnichannel adoption.<\/p>\n The interventions of the companies involved in the OCX conference confirm and operationalize the Research's messages. Despite the different contexts, a common vision emerges:\u2019AI omnichannel<\/strong> It generates value only if grafted onto already structured processes, governance and skills, avoiding purely technological approaches.<\/p>\n Gian Luca Gallo, Chief Commercial Officer of TP Italia, emphasizes how AI is acting as an amplifier of existing organizational characteristics. If introduced into companies that aren't ready, AI risks simply making them more complex and expensive, without improving the customer experience. The starting point, therefore, remains a centrally managed understanding of corporate processes and knowledge.<\/p>\n Vincenzo D'Arienzo, Account Executive \u2013 Collaboration at Cisco, focuses on the evolution of customer service towards intelligent agent-based models. The adoption of autonomous agents and multi-agent architectures opens up new opportunities for scalability and specialization, but also introduces greater complexity.<\/p>\n In this scenario, orchestration becomes crucial to avoid fragmentation, improve the reliability of responses, and maintain a consistent omnichannel experience. A complementary perspective comes from Josef Novak, Chief Innovation Officer & Co-Founder of Spitch, who highlights the need to overcome the contradiction between automation and the human factor.<\/p>\n According to Novak, the future of the Contact Center and Customer Experience lies in models where AI and people collaborate: artificial intelligence helps mediate complexity, supports decisions, and enhances the professionalism of agents, without replacing them. Overall, the contributions converge on one key point: the adoption of AI is not a binary choice between technology and people, but a transformational journey that requires balance, thoughtful design, and strong integration with service models.<\/p>\n The impact of the\u2019AI omnichannel<\/strong> The impact on marketing and business is profound. In digital marketing, AI enables advanced content personalization, dynamic audience segmentation, and automated journey management across multiple channels, including WhatsApp, email, and social media.<\/p>\n For companies, this translates into more effective campaigns, greater message relevance, and better alignment between marketing communications and customer service interactions. The ability to integrate data from different channels\u2014chat, apps, websites, and physical stores\u2014allows them to build a 360\u00b0 view of the customer and orchestrate more seamless and consistent journeys.<\/p>\n From a business perspective, omnichannel AI enables new relationship models: proactive virtual assistants, personalized notifications throughout the customer lifecycle, and dynamic offers based on actual behavior. Intelligent automation frees up agents' time, allowing them to focus on higher-value cases and complex relationships.<\/p>\n In terms of customer experience, AI supports faster responses, advanced self-service, and seamless cross-channel integration, reducing friction and wait times. This directly impacts KPIs like NPS, retention, and average customer value, generating tangible returns on investments in technology and data.<\/p>\n In this scenario, platforms like SendApp become practical enablers of AI omnichannel<\/strong> Business-oriented, with a specific focus on WhatsApp Business and instant messaging. The goal is to transform the chat channel into the operational heart of omnichannel strategies.<\/p>\n With SendApp Official (WhatsApp Business API)<\/a> Companies can securely and scalably integrate WhatsApp into their CRM, marketing automation, and customer service systems. This allows them to orchestrate automated and hybrid conversations, connect AI to omnichannel flows, and centralize data and interactions in a single place.<\/p>\n SendApp Agent<\/a> It allows sales and support teams to collaboratively manage WhatsApp conversations, assign tickets, monitor performance, and combine bots and human agents in a hybrid model. This is the approach recommended by the Observatory: AI augments people, not replaces them.<\/p>\nEnabling factors for a structural omnichannel AI<\/h2>\n
1. Clear strategy and shared roadmap<\/h3>\n
2. Centralized governance and silo reduction<\/h3>\n
3. Skills and partner ecosystem<\/h3>\n
4. Change management and the centrality of the human factor<\/h3>\n
From tactical use to process redesign with omnichannel AI<\/h2>\n
![\"AI](\"https:\/\/sendapp.live\/wp-content\/uploads\/2026\/02\/ai-omnichannel-come-cambia-la-customer-experience-1770713683-357.png\")
<\/figure>\n<\/p>\nFrom Research to Experience: Omnichannel AI in Business Case Studies<\/h2>\n
Omnichannel AI: Impact on Marketing and Business<\/h2>\n
How SendApp Can Help with Omnichannel AI<\/h2>\n