Published : 20/03/2026 - 7 minutes read
AI in the enterprise: from automation to real business transformation
Miguel Ángel Lago Soto
Head of Microsoft Business Apps
Microsoft Business Solutions
Organizations no longer need to ask whether they should adopt artificial intelligence (AI), but how to do so in a way that is useful, scalable, and aligned with the business. Yet many still deploy AI on top of disconnected processes, fragmented data, and applications that lack a shared operational logic. The real risk is not falling behind in innovation, but investing without delivering tangible improvements in productivity, efficiency, or decision‑making—particularly in industries such as manufacturing, retail, and finance‑insurance.
In this context, Microsoft IA Business Solutions enables organizations to modernize critical processes, connect data, and turn AI into a true business capability.
The real challenge is not adopting AI, but integrating it into the core of the business
For years, many companies have digitized specific areas of the business to address immediate needs: automating parts of the sales cycle, improving customer service, enhancing reporting, or modernizing a single application. While these initiatives delivered functional improvements, they often resulted in fragmented environments where systems coexist without a single source of truth or a shared process logic. When AI is layered onto this foundation, its impact remains limited, it may speed up tasks or automate responses, but it rarely transforms the business if the organization continues to operate in silos.
This is the starting point for many organizations today. AI can no longer be treated as a standalone initiative, driven solely by IT or innovation teams. It must become a strategic lever to redesign processes, productivity, and efficiency across the enterprise. The organizations that move fastest are those that successfully align automation, data, applications, and people around a unified operating model.
Market signals clearly point in this direction. McKinsey recently noted that 71% of organizations already use generative AI on a regular basis in at least one business function, while emphasizing that real value comes not from experimentation, but from embedding AI into the operating model.
Service applications: where AI starts to deliver operational impact
In practice, the value of Microsoft IA Business Solutions materializes through the business applications that manage customer relationships, operations, and employees—sales, marketing, customer service, field service, customer insights, finance, supply chain, and project operations. The goal is not simply to add AI features to each application, but to ensure they operate as part of a continuous, connected process.
Transformation does not start with deciding which copilot to deploy first, but with identifying which critical processes lack visibility and coordination. When sales, service, operations, and analytics work on a shared data foundation and a common platform, AI can be applied where it matters most: automating repetitive tasks, supporting prioritization, improving data quality, accelerating issue resolution, and providing contextual insights tailored to each role.
The objective is clear: reduce complexity and accelerate time‑to‑value through end‑to‑end process coverage, enabled by intelligent automation and a scalable, well‑governed architecture.
Manufacturing: control, visibility, and responsiveness in a more demanding environment
Few industries benefit more tangibly from this approach than manufacturing. Manufacturers operate in environments shaped by demand volatility, margin pressure, operational complexity, and the need for end‑to‑end traceability. Yet in many organizations, systems such as MES, ERP, CRM, maintenance, logistics, and after‑sales service remain poorly connected. The result is limited visibility, execution errors, reliance on manual rework, and delayed decision‑making.
Innovation in manufacturing lies in connecting operations, data, and decisions. Microsoft IA Business Solutions provides a unified platform that integrates ERP, CRM, automation, analytics, and AI under a shared process logic. Instead of working with partial information, manufacturers gain end‑to‑end traceability, real‑time visibility, and a stronger ability to anticipate issues, adjust planning, and better coordinate production, supply chain, and service.
Operating on a single platform with connected data, real‑time dashboards, industry templates, and AI‑supported decision‑making has proven capable of reducing cycle times by 15–30%, improving forecasting accuracy by more than 20%, and significantly reducing errors through guided workflows and a unified data model.
The value, therefore, goes beyond automation. It lies in redesigning operations so that data becomes central to every process and AI can act with full business context.
At ITP Aero, a global leader in the aerospace industry, the adoption of a Power Platform governance model designed by Inetum enabled the creation of a Center of Excellence that strengthened security, lifecycle control, and cost optimization. Building on this foundation, the company expanded Copilot usage from an initial pilot to an organizational capability, with more than 1,000 licenses planned for 2026, driving time savings and more efficient access to information.
Discover more AI powered business success stories.
The conclusion is clear: when AI is embedded into a concrete, value‑driven process, it moves from abstract promise to measurable productivity gains.
Finance‑insurance: operational agility without losing control
In financial services and insurance, the priority is clear: move faster without sacrificing control. Organizations need to streamline onboarding, servicing, commercial interactions, and decision‑making while maintaining regulatory compliance, traceability, and strong data governance. Yet many institutions remain constrained by manual reviews, fragmented information, and heavy reliance on legacy systems, slowing operations and increasing the cost of processes such as KYC, AML, and customer management.
In this environment, regulatory pressure and the lack of predictive automation continue to erode confidence in data and hinder the safe adoption of AI.
Microsoft IA Business Solutions addresses this challenge by unifying CRM, service, onboarding, risk, and operations within a secure, governed platform that combines auditable automation with AI capabilities to improve prioritization, forecasting, and productivity.
Market evolution reinforces this shift. In February 2026, Gartner projected that financial organizations using cloud ERP applications with embedded AI assistants could accelerate financial close by up to 30% by 2028, underscoring that AI in management processes is no longer optional, but a structural efficiency lever.
Retail: personalization, efficiency, and a unified customer view
In retail, the pressure is different, but the underlying challenge is similar. Many retailers still operate with fragmented data across e‑commerce, physical stores, loyalty programs, customer service, inventory, and campaigns. This fragmentation makes it difficult to deliver consistent experiences, personalize effectively, or respond quickly to shifts in demand or service issues.
Here, Microsoft IA Business Solutions connects customer insights, commercial operations, service, and analytics to create a unified customer view and enable real‑time action. The benefit goes beyond improving campaigns or speeding up service. It links experience and operations: more accurate personalization, faster case resolution, less friction in returns and orders, and greater visibility into stock levels and fulfillment.
What is holding organizations back and how to move forward with confidence
Despite its potential, adoption does not happen by default. Common barriers persist cultural resistance, uncertainty around ROI, misaligned expectations, poor data quality, lack of governance, and shortages in both infrastructure and talent. In most cases, the true constraint is not technology, but organizational readiness to integrate AI and extract value from it.
Realism is essential. According to a recent IBM study, the leading barrier to AI adoption is concern over data accuracy or bias, cited by 45% of executives. IESE also emphasizes that AI requires management capabilities, judgment, and responsibility, not just technical expertise. The debate is no longer about whether AI will change work, but how people and organizations must evolve to capture its value responsibly.
For this reason, the most advanced organizations follow clear logic: identify high‑impact processes, define measurable outcomes from the start, strengthen the foundation, and support transformation with leadership and upskilling. Microsoft itself sees this moment as pivotal. Its 2025 Work Trend Index shows that 82% of leaders view this year as critical for rethinking strategy and operations, and 81% expect to integrate AI agents into their AI strategy within the next 12 to 18 months.
What does this mean for your organization
The key question is no longer whether AI will transform manufacturing, retail, or financial services. It is whether organizations will integrate AI as a real business capability—or continue to treat it as a collection of disconnected pilots. AI only delivers value when it is applied to solve concrete business problems.
In manufacturing, that means greater control, visibility, and reduced complexity.
In retail, there is a smarter connection between customer, channel, and operations.
In FSI, greater agility without compromising governance.
The next step should not be deploying AI everywhere at once but identifying where fragmentation is hurting the business most—and starting there. Because AI is no longer a technology project. It is a way to redesign the enterprise to operate better.
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