Why Every CEO Should Care About Learning Tech Consolidation Right Now
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Becoming an AI-powered organization requires consolidating fragmented learning technologies into fewer, integrated platforms that cut costs, reduce complexity, and streamline an organization’s diverse technology. Unified systems enable clearer insights, stronger workforce development, and the AI readiness needed to improve efficiency, drive consistent performance, and accelerate innovation at scale.
Across industries, boards are asking what it truly means to be an AI powered organization, and they are asking for it now. CEOs are setting the mandate. The rest of us are responsible for making it real inside complex systems that were never built for this moment.
Becoming AI powered is about fundamentally changing the outcomes we deliver as leaders. That evolution tends to happen in five stages. Before understanding the five stages, it’s critical to explore why consolidation is increasingly important for enterprises.
Why consolidation matters for learning technology
Learning is one of the most fragmented areas of the enterprise tech stack. Over years of organic growth, companies accumulate multiple LMS platforms, multiple content libraries, multiple assessments, multiple proprietary content environments, and multiple inconsistent reporting systems. Learners face a paradox of choice. Leaders struggle to see what skills exist inside the organization. AI cannot identify gaps, recommend the right learning, or guide development because the data is scattered.
When your learning data lives in many systems, you cannot understand your workforce, identify risks, personalize development, or create consistent learning outcomes. AI powered organizations require AI ready people, and AI ready people require unified learning systems.
This is why consolidating learning vendors is foundational.
The 5 stages of becoming an AI-powered organization
Before organizations can truly transform with AI, they typically move through a clear progression of stages.
Each stage builds on the last, unlocking new capabilities and mindsets that shift how people work, make decisions, and innovate. Here’s how these stages can unfold.
1. Efficiency: Doing tasks more easily and automatically
Efficiency is where most organizations begin their AI journey, but it is also where too many stop. Early wins feel meaningful because they eliminate manual busywork and free up valuable time. But efficiency alone does not differentiate a business, it only keeps it moving. Companies that stay here risk mistaking motion for progress, because efficiency is the foundation, not the destination.
2. Speed: Handling core functions faster with AI augmentation
Speed is the moment when organizations realize AI is not just a tool, it is an accelerant. Workflows compress, cycles shorten, and decision making becomes faster. But speed without direction can cause misalignment, because it simply scales the existing problems. True AI maturity requires speed paired with insight, or the organization will reach the wrong destination faster.
3. Effectiveness: Doing things better by recognizing what good looks like and building it into workflows
Effectiveness is the turning point where AI becomes a performance multiplier. Instead of only doing tasks for us, AI helps us do them better by reinforcing what works and identifying which skills, behaviors, and decisions create measurable impact. This requires real data, real examples, and a workforce that understands how to collaborate with AI. Organizations that excel here turn knowledge into a competitive advantage.
4. Consistency: Guiding the reliable execution of best practices
Consistency is where AI becomes the organization’s institutional memory. Instead of relying on tribal knowledge, AI operationalizes proven behaviors so they are repeatable across teams, regions, and functions. This can only happen when the systems behind the business are unified, because AI cannot enforce what it cannot clearly see. Consolidated data and consolidated learning pathways create the stability required for predictable performance gains.
5. Scale: AI guiding the entire company to operate from the same playbook
At scale, AI becomes an orchestrator that aligns teams, workflows, and decisions around a shared model of excellence. This is the highest level of maturity, where AI does not just support the business, it helps transform it. To reach this stage, organizations must consolidate their underlying systems so AI can understand the workforce, the work, and the patterns that drive outcomes. Companies that achieve this will define the next era of growth.
The hidden constraint: fragmentation across tech systems and learning tools
Most companies cannot advance through these stages because their data and learning infrastructure are fragmented. Sales uses one system. CS uses another. Leaders use a third. L&D teams use three or four. Each contains its own logic, its own taxonomy, and its own partial view of the organization. Now compound these challenges within the Enterprise organization where teams run the risk of regional silos within functions and across product lines and you can easily imagine how unstructured investments are being made.
Fragmented data creates fragmented understanding. Fragmented understanding creates fragmented results. You can add AI features or AI agents to every point solution, but AI is only as powerful as the context it can access. When insights stay trapped in separate systems, organizations remain stuck in task level automation rather than business transformation.
This is why consolidation has shifted from initiative to imperative. MIT Project NANDA reports that 95 percent of generative AI pilots are failing, often because the data foundation is too fragmented for AI to deliver meaningful results.
The strategic advantages of consolidating with a single learning partner
Consolidating is not just an operational clean up. It is a strategic unlock for AI readiness and workforce performance. It’s also the most reliable way to concentrate your investments where they drive measurable, compounding ROI.
Streamlined and targeted learning that improves outcomes
In a recent study, we found that only 10% of US-based workers have pursued AI training on their own. Employees cannot waste that time searching for content across platforms. With one unified solution, learners know exactly where to go, what to learn, and how to progress. Quality becomes consistent. Proprietary content can be integrated seamlessly. Learning time is used for learning, not navigation. This leads to stronger engagement and better outcomes.
Cost efficiency and economies of scale
Multiple vendors create overlapping costs, redundant integrations, and heavy administrative overhead. Consolidation unlocks pricing efficiencies, reduces internal IT burden, and simplifies contract management. But cost savings only matter when paired with quality. Consolidation should only happen with a partner that can deliver the full spectrum of enterprise learning needs.
One example of this was seen with Getronics, a Dutch IT services provider with 4,000 employees across 30 global locations, which faced growing challenges in keeping its learning programs consistent. Each region used different training platforms and relied heavily on external providers for certifications, making it difficult to stay compliant with local requirements or track who had completed essential courses. The company needed a unified learning environment that could deliver standardized training at scale while still supporting individual development needs.
By consolidating onto Udemy Business, Getronics replaced fragmented systems with a single platform that improved visibility, streamlined accreditation, and reduced operational complexity. The shift generated £420K (~$540K) in annual savings and helped the company retain 38% more employees while strengthening skills across its global workforce.
A strategic partner that helps you build an AI ready workforce
A learning partner should help you design strategies, not just deliver content. This means dedicated guidance, shared planning, and ongoing support tied to real business outcomes. With a true partner, “learning” evolves from programs that require L&D oversight and management to organizational enablement, tied directly to functional strategy, and shaping how the workforce adapts to emerging skills and new technologies directly within their flow of work.
Unified data, unified insights, and unified action
Consolidated learning creates a single view of skill usage, skill gaps, learning behaviors, and readiness for future roles. Leaders gain clarity on the talent landscape, while AI finally gains the context it needs to personalize development. Unified data leads to unified understanding, which leads to unified action.
Better learning experiences and a stronger learning culture
When learning is unified, it becomes more intuitive, inclusive, and engaging. Local language content improves learner confidence. Consistency reinforces culture. Smooth workflows encourage repeat engagement. A single learning environment becomes part of the company identity, not a scattered set of tools.
Describing how Brazilian financial services firm XP Inc. moved to consolidate and unify its learning and development programs, Sarah Lourenço, Leadership Development at XP Inc., says,
“Part of XP’s culture is to centralize everything to ensure consistent and manageable growth. That’s why we wanted to unify our multiple L&D platforms, offering the right courses based on team goals and creating a learning culture across the organization.”
Simplified Data Management, Compliance, and Security
One system means one privacy process, one compliance framework, and one data protocol. This reduces legal exposure and gives security teams a clearer oversight model. It also removes the technical burden of maintaining multiple custom integrations.
According to the 6sense Buyer Experience report, 58% of buyers said that the need to evaluate how vendors are implementing AI inside their solutions caused them to engage earlier. The increased amount of time buyers are spending up front on long purchase cycles because they need to review AI capabilities and ensure policy compliance can be addressed through consolidation.
How Globant consolidated its learning vendors with Udemy
Globant, a global technology professional services company, integrated Udemy to consolidate its learning vendors. Here are the major findings and takeaways gathered from this from this case study.
The challenge: A lack of unified learning strategy
Globant knew it needed to help its people stay on top of fast-changing tech trends and offer continuously relevant, more comprehensive learning resources across its organization.
But it had no centralized learning and development strategy, creating complexity across multiple systems and teams with different learning strategies. This led to the need to create an online, “consolidated learning environment for everyone to use.”
“We had instances where several teams had developed different learning solutions covering the same thing without realizing it,” explains María José Vera Estupiñán, Learning and DEI Jr Adv at Globant. This lack of alignment also extended to measuring the success of learning programs. “There was not a unique way of understanding what effective learning was and how to measure its impact.”
The solution: Integrating Udemy Business with the organization’s LMS
Globant now uses Udemy Business integrated with its LMS to consider business needs and close any skills gaps — particularly important in the fast-changing technology industry — so the company can meet client requirements on the project level. It also uses Udemy Business to help learners fill any gaps they may have to keep growing in their careers, and work on the skills they need to level up and progress.
Using the data extracted from Udemy Business, Globant can get a holistic picture of learning data and identify its workforce’s learning needs using the company’s own analytics tools.
The results: Universally accessible learning resources
Integrating Udemy Business gave learners greater autonomy in their professional development while supporting the company’s needs.
“Udemy Business helps our people learn the skills they need to be more aligned to what our project, business, and clients require,” says Lucas Campos, Senior Vice President of Technology at Globant. “It gives them deeper knowledge of the areas they need to grow and it helps us ensure they’re always ready for new challenges or projects.”
“It’s a real partnership,” María José explains. “We have bi-weekly meetings with Udemy to go through detailed L&D reports and new strategy considerations. They have the flexibility to adapt to our needs — and that’s crucial for us as a learning team.”
Read more about Globant’s learning story.
Consolidate learning tech to power AI with Udemy Business, and put business performance at the heart of your investment
The shift to an AI powered organization does not start with tools. It starts with your people. And it starts with clarity, consolidation, and connected understanding. Unified systems create unified insight. Unified insight accelerates performance. And unified learning is the foundation for AI readiness across every function.
It is important to remember that consolidation only works with a partner that can deliver the entire learning ecosystem. Udemy delivers a continually updated library of technical and business skills, multimodal learning through assessments, labs, role-play, and instructor-led content, plus the ability to host proprietary training.
Additionally, with global localization, deep system integrations, a strategic partnership approach, and AI-powered recommendations through the Udemy MCP Server, organizations can build learning environments that scale with their goals.
We believe that skills are the new currency, and organizations cannot become AI powered without becoming skills powered.
Request a demo to learn how Udemy Business can help you build an AI ready workforce.
