AI Marketing: Fewer Operational Roles, More Strategy
AI marketing It's no longer a futuristic concept: it's already part of the daily processes of every digital team. Artificial intelligence is profoundly transforming marketing, automating repetitive tasks and shifting value towards strategic analysis and high-impact decisions.
By 2028, according to the latest estimates, three out of five marketing functions will be managed by AI agents. This shift reduces the need for purely operational junior roles and increases the demand for hybrid skills: analytics, creativity, data storytelling, and the ability to guide AI rather than be subject to it.
The result is clear: less time wasted on microtasks like data cleansing, manual reporting, and standard segmentation, and more time dedicated to critical interpretation, storytelling, and growth strategies. In this scenario, understanding how AI is reshaping work is no longer a theoretical exercise, but a prerequisite for remaining competitive in the digital marketing.
AI Marketing and Business Intelligence: From Tools to Analytical Co-Pilots
Business intelligence tools are no longer simple static dashboards: they become the backbone of the’AI marketing. Platforms like Tableau and Google Looker Studio, integrated with advanced cloud ecosystems, are evolving into true intelligent assistants capable of querying complex datasets, synthesizing trends, generating insights, and producing basic narratives.
Tasks that once took hours or days—dataset extraction, source merging, descriptive analysis—are now completed in minutes thanks to automated pipelines. For a junior marketing professional, this means that much of the "operational work" can be outsourced to automation, freeing up time for higher-value activities: contextualization, qualitative verification of insights, development of strategic recommendations, and translation of insights into business actions.
This transformation isn't neutral in terms of employment. Tasks based on fixed and repetitive rules are becoming the domain of machines, while humans retain critical judgment, the ability to ask the right questions, medium- to long-term vision, and decision-making responsibility. Those who integrate these tools into their work will have a clear competitive advantage.
AI Marketing: What Analysts Say About the Future of Roles
Analysts' forecasts confirm the extent of the transformation underway in the’AI marketing. Second International Data Corporation (IDC), by 2028 “three out of five marketing roles or functions will be filled by AI workers, shifting humans and their skills towards strategy and creativity.”.
Between 2027 and 2028, approximately 30% of traditional marketing activities—such as SEO, website optimization, customer data analysis, segmentation, and lead scoring—could be fully automated. This highlights how the role of the "junior market analyst," based on standardized and repetitive analyses, is set to shrink, transform, or in some cases disappear entirely.
However, certain skills that cannot be delegated to AI remain crucial: interpretation, strategic creativity, contextual understanding, brand vision, and customer empathy. Artificial intelligence thus becomes a capability multiplier, but requires professionals capable of mastering its logic, limitations, and ethical implications.
The Four Stages of Automation in Marketing Analytics
To understand how the’AI marketing When redesigning teams and processes, it's useful to look at the typical stages of automation adoption. In the first phase, routines are automated: descriptive analytics, data cleansing, standard reports, and basic segmentation become tasks managed by artificial intelligence models and no-code or low-code workflows.
In the second phase, speed improves and the volume of deliverables grows without the need for a proportional increase in staffing. Reporting, insights, and scenario simulations become more frequent, contributing to faster data-driven decisions. In the third phase, companies begin to reduce headcounts on the most operational profiles, realizing that the "machine" can support increasing loads with fewer human resources.
In the fourth phase, only those professionals capable of supervising AI, interpreting its outputs, translating them into strategy, communicating the results to top management, and ensuring alignment with business and compliance objectives remain. Entry-level positions aren't disappearing entirely, but they're becoming rarer, more hybrid, and much more competitive on the job market.
Strategic skills to stand out in AI marketing
In this context, building the right skills is essential to enhance the’AI marketing. Entry-level positions must develop analytical skills, AI model literacy, narrative skills (data storytelling), and soft skills to work in cross-functional teams. It's no longer enough to simply "know how to use a tool": you need to understand why an analysis is being conducted and how to translate it into decisions.
For mid- and senior-level professionals, artificial intelligence is changing the very way strategy is made. Those who can leverage AI insights, combining them with human judgment, empathy, and innovation, will be in high demand. Skills such as channel orchestration, customer journey design, and impact measurement are becoming crucial.
Equally crucial is the ability to assess the impact of AI on one's role. Questions like "What parts of my job are already supported by AI?" and "In what areas could this support be expanded in the next 2-3 years?" help define a targeted and proactive reskilling plan.
Italy's delay in adopting AI marketing
The Italian context makes the adoption of the’AI marketing even more challenging. The Government AI Readiness Index 2024, compiled by the Oxford Insight think tank, ranks Italy 25th in Europe, behind 13 other European nations. This infrastructural and organizational gap is slowing the spread of artificial intelligence solutions in marketing processes and market analysis.
The real risk is that many Italian companies will miss the "AI-accelerated market research" train, remaining with slower, more costly, and less competitive manual processes. Lack of data governance, information silos, and fragmented data infrastructures prevent them from fully exploiting the potential of AI, especially in areas such as multi-channel attribution, dynamic segmentation, and real-time personalization.
On the other hand, success stories point the way. Global groups like Unilever have already invested in initiatives that leverage AI to accelerate analysis, content production, and local campaign adaptation, resulting in significant reductions in go-to-market times and improved decision-making efficiency. Dove's "Change the Compliment" campaign, which reached 700 million impressions and a positive 94% sentiment in less than 30 days, is an example of how rapid insights and AI can amplify the impact of brand activism and social communication.
Risk, Governance, and Responsibility in AI Marketing
The adoption of the’AI marketing It's not without risks. Software platforms, however powerful, don't solve everything automatically. Misleading outputs in the presence of unclean data, algorithmic biases that reflect distorted historical data, and dependence on opaque vendors are real challenges. This is why companies must invest on three fronts: data infrastructure, skills, and governance.
Data requires centralized catalogs, clear KPI definitions, and robust data quality processes. Skills require ongoing training and reskilling programs for marketers, data analysts, and managers. Governance requires ethical guidelines, policies for responsible AI use, security measures, and compliance. GDPR and emerging AI regulations.
If properly managed, artificial intelligence can transform marketing from a simple sales lever to a core of strategic intelligence for top management. But this requires a cultural shift: recognizing that AI is a powerful tool, not a complete replacement for humans, and that the ultimate responsibility for decisions always remains human.
AI Marketing: Impact on Marketing and Business
THE'AI marketing It has a direct impact on digital marketing strategies, customer experience, and business models. By automating SEO, website optimization, customer data analysis, and segmentation, companies can move from generic campaigns to personalized experiences in near-real time, reducing wasted budgets and improving ROI.
In terms of customer experience, AI allows us to anticipate needs, identify weak churn signals, and personalize messaging and offers throughout the entire customer journey, including conversational touchpoints like WhatsApp Business and other messaging channels. This way, marketing stops being just a push and becomes a continuous, proactive, and contextual service.
For businesses, AI enables predictive models of demand, pricing, lifetime value, and purchasing behavior, enabling faster, data-driven decisions. Companies that integrate AI with their marketing automation and CRM stacks will be able to create seamless funnels, with automatic transitions between awareness, consideration, and conversion, while maintaining human control over strategic decisions.
How SendApp Can Help with AI Marketing
To transform the’AI marketing To achieve concrete results, it is essential to integrate artificial intelligence into the communication channels most used by customers, starting with WhatsApp Business. SendApp It was created precisely to bring automation, data, and AI into conversations, transforming messaging into a true strategic marketing and customer care touchpoint.
With SendApp Official (official WhatsApp Business API) Companies can securely and scalably integrate intelligent bots, marketing automation workflows, and CRM systems, leveraging AI models to segment, qualify leads, and personalize automated messages. Conversational data becomes valuable input for market analysis and the development of increasingly targeted campaigns.
SendApp Agent It enables sales and customer service teams to manage large volumes of conversations in a hybrid human+AI mode, automatically routing requests and leaving high-value cases to agents. SendApp Cloud It is possible to orchestrate advanced automation at scale, integrating data from multiple systems and feeding AI marketing models with real-time insights.
For companies that want to move from isolated experiments to a structured strategy of AI marketing, SendApp offers an integrated ecosystem for designing conversational funnels, automating WhatsApp Business campaigns, and measuring the impact of your actions on business results. Contact SendApp for a personalized consultation or to activate a free trial of their solutions, and bring artificial intelligence to the heart of your customer conversations.
