What lessons can be learned from Microsoft’s cloud transformation?
Editor’s note: This is the first part of a three-part series co-authored by Jim Brisimitzis and Chetan Sharma, exploring the nexus of the cloud/AI and telecom industries from an industry lens. Their decades of experience in the industry and in innovation give us a unique perspective on the lessons we’ve learned and how they can be transferable.
The story of Microsoft’s transformation is a powerful lesson for all industries, and for Telcos in particular. In the mid-2000s, Microsoft was a behemoth of on-premises software with billions of dollars in revenue tied to three-year enterprise agreements. The idea that they would pivot to a consumption-based cloud model was unthinkable to many. But Microsoft looked ahead and saw a new era coming. In 2008, with a market capitalization of just $126.9 billion, they announced their intention to build Azure.
This was a massive, speculative bet. The engineering hurdles were immense, requiring them to turn billions of lines of enterprise code into elastic, multi-tenant services and build data centers capable of absorbing unpredictable workloads while guaranteeing reliability. Investors have since rewarded this bold vision. Today, Microsoft’s market capitalization is nearly $4 trillion, a nearly thirty-fold increase fueled largely by Azure and now AI. They didn’t protect their legacy; they embraced a future that, at the time, was anything but a sure bet.
Over the years, Microsoft and other hyperscalers built deep stacks that stitched together silicon, servers, networking, orchestration, and developer tools into unified, resilient platforms. Now, with the rise of AI, they are reinventing themselves yet again. As Scott Guthrie recently noted when unveiling Microsoft’s Fairwater AI datacenter: “To meet the critical needs of the largest AI challenges, we needed to redesign every layer of our cloud infrastructure stack… where software and hardware are optimized as one purpose-built system.”
The lesson for Telcos is clear: while they have long been known for delivering reliable connectivity, today’s market increasingly values the software-driven agility, scalable infrastructure, and rapid innovation that hyperscalers have perfected. Microsoft recognized early on that for the sake of their long-term success, they needed to control the platform, not just the components they bought from vendors. This is true for all hyperscalers and large SaaS providers — a time-tested playbook with highly rewarding outcomes. By learning from this playbook, Telcos can reposition themselves for sustained growth, improved efficiency, and renewed competitiveness.
Telcos have historically depended on vertically integrated solutions, where hardware and software come as a tightly coupled package from a handful of vendors. This has created a high bar for network availability, but it has also limited flexibility and innovation. Contrast this with the approach of hyperscalers, which meet their vendors with specific requirements and a vision for a requirements-driven platform.
Software is the great neutralizer, redefining the rules of every industry. Hyperscalers used software to abstract away hardware, build platforms at unprecedented scale, and then leverage those platforms to disrupt industries from retail to finance. Crucially, they also used it to disrupt themselves, constantly reinventing their own products and services before competitors could. Today, AI represents the next evolution of this playbook. Hyperscalers are re-architecting their stacks for AI at massive scale — from silicon and servers to data fabrics and application models.
In a joint GitHub + Accenture study, developers using Copilot accepted ~30% of its suggestions, with 90% reporting they committed code suggested by Copilot. The message is simple: staying still is a sure bet for irrelevance.
Microsoft’s approach to Azure follows similar “reinventions” of other global technology players including Oracle, SAP, Cisco, and VMware, all of whom have had to pivot their portfolios from on-premise license-driven models toward cloud, SaaS, and consumption-based scalable services.
There are countless lessons to draw on, but we have distilled four that are critical for Telcos to consider. Each of these lessons is central to the hyperscaler playbook and can enable Telcos to transform their business models.
- Rethink Vendor Relationships: Embrace Disaggregated, Software-First Architectures: Microsoft’s pivot to Azure demonstrated the power of a disaggregated architecture. By decoupling hardware from software, Telcos can unlock modularity, expanded vendor choice, and accelerated feature delivery. They can follow suit by embracing open-source cloud-native network functions, deploying white-box hardware, and deliberately reducing proprietary dependencies. This would not only lower upgrade costs but also enable faster, more agile modernization across their networks. This is the first step for Telcos to become “TechCos,” where their network truly becomes a value-generating platform for others to leverage and build on.
- Embrace True Multi-Tenant, Self-Service Platforms: What sets hyperscale clouds apart is their ability to serve thousands of tenants securely and independently on shared infrastructure. With strong isolation and easy, self-service provisioning, they have created ecosystems where partners, developers, and customers can all innovate in parallel. Telcos can replicate this playbook by re-architecting networks and edge resources as cloud-native, API-driven platforms. This means offering fine-grained tenancy isolation and building self-service portals for internal teams and independent software vendors. The payoff is a fundamental repositioning: from commodity connectivity providers to true platforms that catalyze ecosystem innovation.
- Adopt Consumption-Based Billing and Prove It with Financial Contrasts: Cloud players didn’t just redefine technology; they rewrote the economics of IT. Their shift to consumption-based pricing aligned costs with actual usage, encouraged experimentation, and fueled ecosystem growth. Telcos can make the same pivot. By offering pay-as-you-go models for edge AI inferencing and APIs, they can create a platform where developers and partners actively build. Done right, consumption-based billing can reposition telcos in the eyes of investors, transforming them from debt-laden infrastructure players to scalable, software-driven platforms with stronger growth potential.
- Instrument Programmable Platform for Enterprise Opportunities: 5G was supposed to be the enterprise cycle; however, most operators have hardly gone beyond just offering 5G lines to the enterprises as their “core” enterprise strategy. To be able to build and grow a sustainable enterprise business, one has to focus on how vertical industries work and want the telecom world to engage with them. Service providers who build the underlying platform of connectivity and compute that is accessible and programmable to the needs of thousands of enterprise roadmaps.
In less than two decades, Microsoft’s market cap has increased nearly thirty-fold, fueled by Azure and AI. Telcos stand at a similar critical juncture. The lessons from hyperscale clouds are clear: rethink vendor relationships, re-architect as multi-tenant platforms, and embrace consumption-based business models. These shifts won’t just modernize infrastructure; they will redefine telcos’ role in the digital economy, moving them from commodity connectivity providers to agile, software-centric platforms.
In our next piece, we’ll expand on this idea of “platformization,” exploring why Telcos must rethink their identity and expand their horizons, how they can leverage private 5G and data sovereignty as entry points, and what it means to become a true platform provider rather than a capital-intensive utility. If one doesn’t ready their platform strategy in the 5G cycle, fine-tune it, and start generating new revenue, it certainly won’t happen in the 6G decade.
Finally, in the third and final piece, we’ll turn to the AI inflection point: examining how AI isn’t just a cost saver but a potential growth engine, and why Telcos — uniquely positioned at the edge of data — have an opportunity to become central players in the enterprise AI economy. We will prove it with examples of live use cases.
Together, this series will outline not just lessons learned but a playbook for how Telcos can reinvent themselves for the next decade of disruption. Our goal is to inspire a global conversation with intentional provocation, because in the digital age we live in, change is inevitable, and software will be the enabler. We encourage everyone reading this series to share your thoughts and challenge our thinking.
