Reinvent IT: Build the Future — Don’t Rent It.

In the era of AI, the question for every business leader isn’t whether to transform — it’s whether to do it smart or stay stuck. We are at a strategic inflection point where the traditional IT playbook is not just outdated; it’s a liability. When fintech giant Klarna announces plans to “Shut Down SaaS Providers” and replace them with internally built AI-centric solutions, it’s not just a headline—it’s a declaration that the ground has shifted. It’s time to ask a fundamental question:

What if you could totally rewire your Technology Operating Model? What if you reduce external cost and rapidly invest into your in-house talent, to take ownership and drive innovation?

The answer is clear: a strategic shift from being a technology ‘Renter’ to a ‘Builder’ cuts total cost of ownership, funds market-leading innovation, and delivers proven financial results.

The Financial Imperative: Why Builders Are Winning

The evidence for the “builder” model is no longer theoretical; it’s written in the financial reports of the The evidence for the “builder” model is no longer theoretical; it’s written in the financial reports of the world’s leading digital banks. The institutions that have invested in building their own technology platforms are not just out-innovating their peers—they are dramatically out-performing them on the bottom line.

Consider the new generation of neobanks:

• Starling Bank (UK) achieved a remarkable £301 Million in pre-tax profit, demonstrating a 55% year-over-year increase by competing effectively with a lean, in-house cost base.
• Nubank (Brazil), running on its in-house platform, posted an incredible $527 Million in Net Income in a single quarter, driven by a cost-to-serve that is 85% lower than traditional banks.
• Revolut (UK-Global) has surpassed $2 Billion in revenue by leveraging its proprietary platform to rapidly launch and monetize new services.

The data paints a stark picture. While builders like Nubank, Revolut, Monzo, and Starling are posting significant profits, neobanks reliant on third-party vendors, like Chime and N26, have reported substantial net losses. Even incumbent institutions are recognizing this shift; Standard Chartered, for instance, built its own in-house, cloud-native core banking platform, enabling rollouts across all markets with a low USD-Million number per year.

AI makes the difference – it really does!

AI’s impact on software development is direct, tangible, and happening now. This isn’t about replacing developers; it’s about giving them superpowers. Today, development effort in many areas can be cut by up to 90%, and in others by at least 20%. This productivity gain is critical for reallocating resources toward innovation. This is real experience from my own teams, and from my global “CTO” Community.

The real revolution comes from AI agents that actively expand your platform. Think of an agent tasked with, “Roll out the ‘Promotions’ feature to the German market.” It wouldn’t just translate text; it would check for GDPR compliance against an internal knowledge base, generate region-specific user journeys, and create the feature flags and deployment configurations for review. This is what it means to build an AI-native platform. It’s a shift from your team doing all the work to your team directing intelligent agents that execute. This is how you move from month-long release cycles to shipping valuable code multiple times a day.

his AI-native approach is not theoretical; it is being implemented today with readily available technology. Building your own platform allows you to integrate best-in-class tools to create capabilities that are impossible to achieve with rented software. For example:

• Automating Complex Operations: By using an in-house platform, you can deploy collaborative AI agents built with development kits (like Google’s A2K). These agents can be managed by your business teams through visual workflow builders (like N8N), allowing you to automate sophisticated, cross-departmental processes.
• Achieving Marketing Agility: Your marketing team could directly integrate cutting-edge tools like Google Cloud’s video analytics (VEO) and AI image generation (Imagen) into your proprietary MarTech stack. This enables them to create and launch new campaign assets daily, responding to market trends in hours, not weeks.
• Innovating in Core Business Logic: In financial services, building your own platform allows you to leverage alternate data sources for credit risk analysis. This creates a proprietary lending model that is more accurate and inclusive, opening up new market segments that are inaccessible to competitors who rely on standard, off-the-shelf risk engines.

The New Playbook: Leaders vs. Laggards

The adoption of AI and future workplace technology is dramatically changing the approach to strategic IT development. The difference between leaders and laggards is becoming a chasm:

This new model isn’t just about technology; it’s about talent and structure. The role of managers shifts from simply managing people to becoming senior subject matter experts who guide automated reporting. In this environment, where the “1-person-AI-unicorn” is becoming a reality, the ability to innovate rapidly with a strong in-house talent base is paramount.

Technology Strategy and Innovation: Driven by Big Tech! Only!

Your New Tech Strategists: Follow the Builders, Not the Analysts

For decades, your organization’s technology strategy was likely dictated by analyst reports and expensive PowerPoints from management consulting firms. That playbook is officially dead. Today, BigTech sets the pace for R&D and tech innovation—they are the benchmark. While analysts write theories about technology, companies like Google, Microsoft, AWS, Tencent, Alibaba, and Nvidia are the ones deploying it at planetary scale. Their strategy isn’t a theory in a slide deck; it’s committed code running in production. Organizations must track their direction and selectively partner where it is strategic. This means following their ‘Go To Market’ announcements, investor presentations, and engineering blogs—not just their marketing.

This intelligence has a direct impact on the IT and Technology Strategy of organizations, which in turn triggers new capabilities across all business domains.

Leveraging Their Power Through Open Source

So how do you leverage BigTech’s power without their multi-billion dollar R&D budget? You embrace their most disruptive strategy: Open Source. These players are doubling down on open-sourcing their foundational tools—from Google’s AI frameworks to Meta’s language models and the entire Hugging Face ecosystem. This is a strategic gift to in-house engineering teams. It’s your invitation to stop paying for black-box vendor solutions and start building with the best tools on the planet, often for free. This is the ultimate builder’s advantage: while your competitors pay consultants to be told what’s possible, your engineers can be busy building it with the very same technology that powers BigTech itself.

Innovation versus Commodity

A key principle in modern technology strategy is distinguishing between pure commodity services and true innovation. For most organizations, success lies in effectively managing a combination of both.

Core, customer-facing capabilities—such as a Core Banking platform, CASA, or lending platforms—represent the innovation layer. These are the differentiators, developed in-house by leveraging open-source technologies to create a proprietary advantage.

Conversely, typical ERP components like Finance/General Ledger, Human Resources, and Procurement are often commodities. These functions should be sourced from best-in-class SaaS platforms, implemented without customization, and rolled out rapidly (e.g., within six months) to minimize cost and complexity. If such a platform appears to require extensive customization, it is a red flag: either the business need is overstated, or the function is not a commodity and should be reclassified into the innovation layer.

Defining which capabilities belong in each category is not a technical detail but a foundational strategic decision that must be resolved during the strategy phase.

A New Technology Operating Model: Your Blueprint to Build

Making the transition from renter to builder requires a new Technology Operating Model designed to reduce costs, accelerate delivery, and drive innovation. But this model is founded on a principle that precedes any technology decision: trust. It requires business stakeholders to empower leaders they believe in to build teams and execute the mission. This model stands on five pillars:

1. Build Core In-House Talent: Hire doers—engineers, data scientists, and AI specialists. Build small, cross-functional squads with deep ownership. Focus on attracting and growing top-tier talent within an empowering, experimental culture.
2. Shift Spend Strategically: Reallocate budgets directly from vendor licenses to builders. Invest in innovation, not integration. Only outsource true commodities.
3. Develop an AI-Native Platform: Own your Intellectual Property; don’t lease it from vendors. Adopt an Open Source-first policy. Embed AI agents at the core of your operations.
4. Operate as a Product Organization: Prioritize dynamic roadmaps over rigid, long-term projects. Drive genuine product innovation, not just process automation. Measure what matters: Time-to-Value, In-House %, AI ROI, and TCO/unit.
5. Try / Innovate: Experiment with new technology relentlessly. Partner with startups and open-source communities. Foster a culture of learning and rapid iteration.

From Blueprint to Reality: Case Studies in Building

This model isn’t just theory. It’s a proven approach I have implemented to drive transformation at world-class organizations.

• Case Study 1: Transforming a Global Bank (Standard Chartered) As Global Head of Architecture and IT Strategy, we moved to in-source the development of critical platforms like Core Banking, CASA, and Payments. This “builder” approach allowed the franchise to rapidly launch new products globally and fueled the bank’s innovation strategy, leading to the creation of SC Ventures, a successful incubator for new business models across Asia, the Middle East, and Africa.
• Case Study 2: Powering a Retail IPO (Central Group) At Central Group, I was tasked with building a digital startup from the ground up. I grew the team from a single employee—me—to over 450, building out capabilities in Digital Commerce, O2O, and Customer Insights. This new “built” engine grew to generate approximately 20% of Central Retail’s revenue, enabling the group to launch the second-largest global retail IPO. This included a joint innovation with JD.COM to launch a new eCommerce Marketplace and FinTech venture.
• Case Study 3: Rescuing a High-Stakes O2O Ecosystem Working with a major conglomerate through my firm Pivot Digital, we tackled a business locked into costly vendor SaaS platforms and a failing O2O ecosystem built by a top-tier consultant. The situation involved high costs and technical issues that inhibited growth. We redesigned the architecture, established a new operating model, and helped build a world-class team. This intervention led to a spectacular turnaround, driving significant growth and establishing the business as a regional online leader.
• Case Study 4: Reinventing Luxury Retail (Siam Piwat Group) Most recently, I partnered with Siam Piwat Group, a top global luxury mall operator, to launch Xponential as the group’s innovation arm. Our mission is to build in-house expertise to execute our most innovative ideas. We are strategically moving from a vendor SaaS platform to a proprietary, in-house platform to lower costs, increase speed-to-market, and build features unique to our business strategy. This journey is already a tremendous success, with the OneSiam SuperApp now recognized as one of the best and most innovative global mall apps, rapidly incorporating blockchain and AI.

There are many other Bank and Retail Industry examples where this model works and drives change.

The Future is Built

Today, Global BigTech companies like Google, Microsoft, and AWS are setting the pace for R&D and tech innovation. They are the new benchmark… Organizations must track this direction and partner selectively where it is strategic.

But the blueprint, the technology, and the financial models are only part of the equation. The final, and often highest, hurdle is one of conviction. It’s the confidence for an organization to look at a complex technology business built by a competitor and declare, ‘If it can be done, we can do it too.’

This requires business stakeholders to trust their leaders—people like me—to build the necessary capabilities. It transforms the core question from a doubtful ‘Can we?’ to a strategic ‘Should we?’ Once you decide that building makes sense, the unwavering belief that you can is the essential fuel for true transformation.

The focus is to reduce external cost and reinvest into in-house capabilities to execute this strategy to own and innovate.

The path to sustainable growth and market leadership is clear. Don’t Rent the Future. Build It.

—

Axel Winter puts the concepts from this article into practice in his current leadership roles. As CEO of Xponential, part of the leading global luxury mall operator Siam Piwat Group, he applies this strategic framework to the retail industry. He is also the CEO of Pivot Digital, a global consulting firm that advises top banks, retailers, and FinTechs on how to implement this same model—distinguishing commodity from innovation—to accelerate their own transformations.His perspective is shaped by previous roles as the Global Chief Architect and Head of IT Strategy at Standard Chartered Bank and GE Capital, and as a consultant with Accenture and Deloitte.

His perspective is shaped by previous roles as the Global Chief Architect and Head of IT Strategy at Standard Chartered Bank and GE Capital, and as a consultant with Accenture and Deloitte.