Accelerating AI transformation with Microsoft

April 2026

It’s no secret that organizations are struggling to scale their use of AI. Only 8% of executives report having fully scaled their AI projects, while just 7% are scaling agentic architecture across the enterprise.¹

The challenges business leaders face are both technological and cultural. Scaling AI adoption means making new tools quickly and securely available to people across the business. It also means making sure those new tools feel familiar and intuitive.

This is why, for many organizations, Microsoft business applications will prove a powerful accelerator for AI adoption at scale.

Embedded in software that everyone in the business already uses, Microsoft’s AI tools offer a relatively easy win for businesses looking to foster an AI-first culture. As AI-enabled personal productivity becomes the status quo, transformation leaders can aim higher, lifted on a wave of popular acceptance. Building on the same Microsoft platforms they can start using AI to guide scaled AI adoption – and accelerate away from peers still mired in a landscape of isolated AI pilots and failed PoCs.

Speeding up the early stages of AI adoption

Every large organization is, by its nature, a highly diverse operation. Processes, systems, and subcultures vary between teams, departments, and countries. This is one reason why scaling a new, transformational technology is always a complex proposition.

But in many organizations a common thread connects everyone who sits down at the start of the day and boots up a desktop or a laptop: Microsoft business applications. Whether they’re writing an email with Outlook, organizing files on SharePoint, or using a CRM built on Dynamics, they now have at least one AI tool at their fingertips: Microsoft 365 Copilot.

When organizations start strategic AI adoption with the capabilities embedded in the Microsoft solutions they already use, they are able to get moving fast then rapidly build momentum:

The technical hurdles are low. Implementing Copilot is straightforward when you are already using the Microsoft software ecosystem.
Compliance and risk concerns are minimal. From a data governance and security perspective, the business is simply extending the use of an existing platform.
The UX is welcoming. The AI is wrapped in familiar interfaces, and integrated with software solutions people know how to navigate.
Multiple models are available. Microsoft tools increasingly support third-party AI models. Earlier this year Microsoft announced Copilot Cowork, which integrates the technology behind Claude Cowork from Anthropic.²

In this first phase of strategic AI adoption, organizations must take proactive steps to win hearts and minds. One in four organizations say resistance to change is a barrier to AI-driven transformation. Both simple inertia and anti-AI sentiment often need to be overcome.³

Success will depend on bringing people together with their co-workers, and presenting personal productivity as a unifying goal. User groups are a helpful mechanism, providing a structured opportunity for colleagues to discuss shared tools such as Copilot, and exchange their experiences, tips, and tricks. Coupled with targeted training, such peer-to-peer forums help AI tools to click and AI-enabled habits to stick. Before long, organizations are in a position to identify and elevate AI champions, and parachute them into teams where adoption is lagging.

As everyone in a business becomes comfortable using AI in their workflows, more advanced use cases feel like less of a reach. After all, the step from asking AI’s help with writing an email to trusting AI to produce a document or inform a decision is relatively small, especially when you can do both within the same copilot.

In this way, organizations can quickly build a robust cultural and technological platform for the next phase of their AI transformation: the targeted scaling of AI across roles and core business processes.

Using AI to drive strategic AI adoption

Attempts to scale AI often stall from a lack of clear strategic direction. Transformation leaders struggle to identify the most valuable AI use cases and to chart a clear path to demonstrable business outcomes. This is a challenge that AI itself can help to address.

BearingPoint’s own GenXplore platform provides a great example, as a tool that uses AI-powered analysis to accelerate AI-driven efficiency.⁴

Based on Microsoft technology, GenXplore analyzes an organization's existing data, including job descriptions, process documentation, and organizational charts. Using the organization's preferred LLM, it pinpoints where copilots, agents, and other forms of AI can deliver the most significant value. With this objective, data-driven insight, organizations are able to develop AI transformation roadmaps that prioritize quick wins, build momentum, and expedite ROI.

In a recent study, GenXplore analyzed over 1,000 different jobs within a large European transportation company. It uncovered significant opportunities to support middle management roles with both Microsoft Copilot and more specialized AI tools. Simply by using AI to augment everyday tasks from performance monitoring to resource planning, the organization stands to enhance both decision-making and process efficiency.

Combining AI-driven insight with human expertise

Organizations can further de-risk and accelerate their AI transformation by combining AI-driven insight with the right human expertise.

As AI use cases become more ambitious, businesses must lay some additional foundations. Data governance and security strategies must be revisited and developed. Key workflows and core processes must be redesigned. Top-down change must be carefully managed.

When seeking a partner to support this vital work, all the traditional best practices apply. Organizations should select a partner with close ties to Microsoft and deep expertise across its solution ecosystem. They should favor those with practical experience in their industry, and the ability to shape AI adoption with AI-driven tools.

An ideal partner will be able to propel an organization through these initial phases – establishing personal productivity, conducting a targeted scale-up – before facilitating enterprise-wide AI roll-outs, and the ongoing use of Microsoft solutions as an engine for continuous transformation.

To fully support this multiphased transformation journey, BearingPoint has consolidated its own award-winning Microsoft delivery and consultancy expertise under one roof, creating a dedicated Enterprise Microsoft Transformation practice.⁵