Fawad Qureshi, Global Field CTO, Snowflake, on realising possibilities for innovation in this new AI era

Without cloud migration, businesses face the end of innovation. In this new AI era, businesses operating within the closed architectures of legacy systems do not have the flexible, data-driven foundation to engage with these new technologies and ensure a strong pipeline of necessary innovation. And as AI continues to evolve, those not able to keep pace with innovation risk being left behind. 

Cloud migrations are the foundation to modernise and drive business growth over the long term. When organisations migrate to a cloud-based environment, it’s crucial to focus on the tangible business value a migration will deliver, rather than simply shifting from one system to another. Moving a company’s customer-facing applications and all of their data to a cloud-based environment has the benefits that are increasingly real and measurable.

Migration isn’t just a Plug and Play approach – Which migration fits your needs?

There are two approaches to cloud migration, broadly speaking: horizontal and vertical, each with their own benefits and potential challenges. A vertical approach sees organisations migrating applications one by one: this approach is a good choice if certain systems have to be prioritised, or if the applications being migrated do not have many interdependencies. Vertical migration allows for focused efforts and risk management on individual systems, and requires fewer resources. Horizontal migration moves entire system layers at the same time. This is the best solution when businesses have tight deadlines to retire legacy systems, or if their systems are tightly integrated. Horizontal migrations tend to be faster by allowing for parallel work streams, but they require more technical expertise. 

Organisations often adopt a mixture of the two approaches, for example, horizontally migrating important systems such as data platforms, while taking a vertical approach to customer-facing applications. Whatever approach an organisation takes, it’s vital that the migration also includes a culture shift, preparing employees to adapt to new, consumption-based models and the possibilities of the new technology. Migration is also just the start of the journey, unlocking the potential of AI-driven use cases and seamless data collaboration, including new ways to achieve business value. 

Before diving straight in, ensure it’s with a Data-First Mindset

When migrating to the cloud, a data-first approach is essential. For those acting as the catalyst for change, whether that be IT managers or even CIOs, data must be front of mind before planning any successful migration.  Understanding how data is used within the organisations, including its structure, governance needs, and how it delivers value and business outcomes, is imperative. This applies doubly when it comes to large, complex systems with many interconnected applications. 

Before migrating, businesses must comprehensively assess their current ecosystem. It’s imperative that the end-to-end business product survives the migration, intact. Organisations should maintain internal control over core competencies around data, such as business process knowledge, data governance and change management. These areas include institutional knowledge that external parties may not grasp. Businesses should also maintain direct oversight over compliance requirements and risk management. 

Technical activities such as cloud infrastructure optimisation, performance testing, and specialised migration tooling are something, by contrast, that can be handled by external expertise. Code conversion can also benefit from purpose-built tools that use technologies including AI. Technical parts of the immigration tend to evolve rapidly and require specialist knowledge, so are ripe for outsourcing. While doing so, those steering the migration need to ensure clear governance around outsourced activities, including regular knowledge transfer sessions. 

Different parts of the business all have a role to play: IT and engineering lead on technical implementation, handling the technical side of business requirements, while finance will identify ROI opportunities and manage cloud costs. It helps to create a cross-functional steering committee with representation from every department to ensure that different areas of the business are aligned and ready to address challenges. 

Adaptability and Flexibility is the key to business longevity 

Migration is never one-size-fits-all, and business leaders should be prepared to be flexible and adapt. There are multiple kinds of horizontal migration, from a simple ‘lift and shift’ focused on moving systems as they are to a ‘move and improve’ where migration is followed by optimisation to reduce technical debt. They should be ready to adapt at their own pace, choosing data platforms which offer agnostic architecture and the freedom to choose between data models and tools to ensure minimal disruption.

Flexibility is also important in choosing the tools used for migrations. Flexible data platforms will offer the support businesses need to deal with collaboration and governance frameworks. For businesses operating in EMEA, where different countries can have varying policies, pay close attention to issues around data quality, security and compliance, particularly when it comes to data sovereignty and issues around European data residency. 

A Shared Destiny

The shift to the cloud fundamentally changes security. The traditional cloud ‘shared responsibility’ model clearly demarcated duties between the provider and the customer. However, a more advanced approach is emerging: the ‘shared destiny’ model. This model recognises that in the event of a breach, reputational damage affects both parties. This shared risk incentivises the cloud provider to be a more proactive partner, actively helping customers strengthen their security posture rather than simply managing their own side of the demarcation line.

As ‘destinies’ intertwine, you help eliminate the vulnerability created due to password simplicity. Put simply, in a ‘shared responsibility’ model, the cloud provider is only responsible for securing infrastructure, while the customer remains responsible for securing data and apps in the cloud, as well as for configuration. In a ‘shared destiny’ model, the cloud provider plays a more proactive role to ensure that their customers have the best possible security posture. 

Taking a ‘shared destiny’ approach allows businesses to be more proactive in securing data, using approaches such as multi-factor authentication, secure programmatic access and more comprehensive cloud monitoring services. Choosing a modern, AI-driven data platform offers the best security foundations here, offering security controls across cloud service providers and the entire data ecosystem. 

A Pathway to Growth

In today’s world, the bigger risk is standing still. Nothing changes if nothing changes.

If organisations are holding back on innovation due to technological limitation, then the time to migrate is clear. There is no need to face an end to possibilities when the path towards success lies in reach, offering an opportunity to bring businesses up to date with modern requirements, and pave the way for the adoption of technologies such as AI. 

However, as we’ve seen, it’s not just a case of plug and play. Organisations must ensure a flexible, data-driven approach to migration, while keeping security front of mind via a ‘shared destiny’ approach. To deliver this, the right choice of a modern, flexible data platform will ensure the whole organisation can work together effectively and deliver a path to future innovation and growth. 

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Interface issue 68 is live featuring Microsoft, Virgin Media O2, CIBC Caribbean, Telkom, Zoom, ServiceNow, Snowflake and more

Welcome to the latest issue of Interface magazine!

Click here to read the latest edition!

Driving Business Transformation Through Cloud & AI

Microsoft’s Shruti Harish, Head of Solution Engineering for Cloud and AI Platforms across the tech giant’s Manufacturing and Mobility vertical, talks to Interface about how to achieve successful AI implementations augmented by Cloud. Our future focused fireside chat covered everything from driving value through cloud modernisation to responsible AI.

“Leaders should align AI initiatives with clear business outcomes and foster a culture that embraces change. The focus is shifting toward AI-operated, human-led models where intelligent agents handle tasks and humans guide strategy.”

Virgin Media O2: Democratising Data as a Cultural Movement

Mauro Flores, EVP for Data Democratisation at Virgin Media O2, talks to Interface about the leading telco’s data journey and how it is supporting colleagues to innovate faster, make smarter decisions and deliver brilliant customer experiences.

Data-driven insights are essential. They’re helping power our decisions like optimising our network performance, anticipating outages before they happen, identifying and preventing fraud, personalising offers and pricing to build customer loyalty, and forecasting demand so we invest in the right things.”

CIBC Caribbean: Shaping the future of Banking in the Caribbean

Deputy CIO Trevor Wood explains how CIBC Caribbean is blending technology, culture, and customer-centricity to deliver seamless digital experiences across the region with a ‘Future Faster’ strategy.

“We want to lead in every market we operate, build maturity across our practices and be architects of a smarter financial future for all.”

And read on for deep AI insights from ANS’s CIO on why AI isn’t just for big business, Emergn’s CTO on how your business can get AI-ready and Kore.ai’s Chief Strategy Officer on taming AI-sprawl with governance-first platforms.

We also hear from Celonis, Snowflake, ServiceNow, Make and Zoom with their tech predictions for 2026 and chart the key dates for your diary with global networking opportunities at the latest tech events and conferences across the globe.

Click here to read the latest edition!

  • Artificial Intelligence in FinTech
  • Data & AI
  • Digital Payments
  • Digital Strategy
  • People & Culture

ServiceNow, Celonis, Snowflake, Zoom and Make deliver their 2026 tech predictions for emerging technologies, including agentic AI, the role of the CIO, data governance, autonomous operations and more…

Louise Newbury-Smith, Head of UK&I at Zoom

AI elevates both manager effectiveness and employee autonomy

Moving forward, AI will simultaneously strengthen managerial capabilities and empower employees to work more autonomously. Managers will gain real-time insights into workload distribution and collaboration patterns, allowing them to support wellbeing, performance and development, without relying on manual check-ins. At the same time, intelligent workflows will give employees greater control over how they work enabling them to personalise tasks, streamline processes and focus on higher-value activities. This dual uplift will reduce friction, improve team culture, and create a more balanced workplace environment.”

AI fluency becomes the new foundational skillset

“The next phase of upskilling will blend technical and human capabilities. Employees will be expected to understand how to collaborate with AI, interpret its recommendations, and challenge outputs when necessary. Training and change management will be essential to realising the full value of these emerging tools. For IT teams, this means not only deploying the technology but also leading adoption across the workforce.

Darin Patterson, Vice President of Market Strategy at Make

2026 will be the year businesses of all sizes finally turn AI’s promise into measurable value

“Companies will shift from experimentation to dependable automation that powers productivity, decision-making, and customer experience behind the scenes. AI will be judged less by novelty and more by real outcomes, whether orchestrating marketing campaigns, managing workflows in professional services, or enabling personalised, frictionless customer interactions. With maturing standards like Model Content Protocol and Agent2Agent moving into widespread use, organisations will gain the stability and coordination needed for scalable multi-agent systems that quietly keep operations running.

As these technologies advance, AI’s complexity will fade into the background. Concepts like embeddings and prompt engineering will be built into everyday tools, allowing smaller businesses and non-technical teams to deploy automation quickly and confidently. In 2026, the winners will be the companies using AI for practical, connected automation that drives results, while standalone chatbots and overly complex approaches fall away. The future belongs to businesses that stop chasing hype and start running on AI.”

Cathy Mauzaize, President, Europe, Middle East and Africa (EMEA) at ServiceNow

The governance vs. speed tension will define leadership in 2026 

“As AI becomes core to how organisations operate, leaders will face a growing challenge: how to maintain trust without slowing down innovation. Across EMEA, this balance between governance and speed is becoming the defining measure of AI maturity. The EU AI Act marks a turning point that moves regulation from theory to practice. But rules alone won’t create responsible AI. The real test will be how organisations translate compliance into everyday practice, embedding accountability and transparency into workflows, data, and decisions.  

The University of Oxford’s Annual AI Governance Report 2025 found that leading organisations are embedding governance directly into workflows, not treating it as a compliance exercise. In doing so, they’re maintaining innovation speed while reducing AI-related risk. 

The leaders who succeed will treat governance not as a brake, but as an engine of trust and resilience. They’ll build cultures where transparency, explainability, and ethical use are built in, not bolted on. They’ll use clarity to move faster, not slower. Doing this will require a central, single-platform lens of LLMs, AI agents and workflows.  

This is what will separate compliance from competitiveness. AI must remain fast enough to drive innovation yet be governed tightly enough to earn trust. The leaders who get this balance right will define the next phase of growth, proving that responsible AI and rapid progress can coexist.”

CIOs must lead the enablement of agentic AI with a view to future risk 

“2026 will mark the rise of Agentic Platforms – networks of intelligence that blend human and machine work to drive speed, accuracy, and innovation. These agents will increasingly operate alongside people, managing workflows and simplifying complexity – not to replace human judgment, but to strengthen it.  

Yet, as this new layer of work evolves, so does a new layer of risk. The challenge will no longer be shadow IT, but ‘shadow AI’ – models and agents developed outside governance frameworks. This creates vulnerabilities for compliance, privacy, and security. Although regulations are evolving across regions, innovation is already moving faster than policy. CIOs and boards will need to anticipate, not react, staying one step ahead of regulatory change to avoid future disruptions. Agility will be the differentiator. 

The leaders who succeed will do so by adopting flexible, adaptive platform architectures, able to connect data, governance, and decision logic by design. These platforms will allow organisations to monitor, verify, and coordinate AI activity across every functions, ensuring that trust, compliance, and performance advance together.”  

Peter Budweiser, General Manager Supply Chain at Celonis

The race to autonomous operations will be won by orchestration

“Enterprises have spent a decade automating tasks. But in the agentic future, the differentiator won’t be how many tasks you automate, it will be how well you orchestrate outcomes. In 2026, leaders will shift from fragmented automation to coordinating AI, people and systems across the entire workflow. This is the only way to transform business processes into truly autonomous operations.

Supply chains will become the proving ground for orchestration. AI will dynamically reroute shipments, rebalance inventory, surface capacity constraints, and coordinate suppliers and planners in the same loop – turning fragile networks into intelligent, adaptive ecosystems that are able to respond instantly to tariffs, disruptions and volatility.

The strategic driver behind supply chain transformation is no longer just cost – its competitiveness. Orchestration lets companies coordinate AI agents, humans, and systems in real time, so their supply chains become more agile, more efficient, and better able to support new business opportunities.”

Dan Brown, Chief Product Officer at Celonis

The AI revolution will run on context

“After years of experimentation, companies will realise that AI can’t improve what it doesn’t understand. In 2026, competitive advantage will shift to organisations that give AI the operational context it needs – a living digital twin that shows how the business actually runs. This is how AI learns to sense, reason, act, and improve responsibly.

Context-aware AI will reshape supply chain decision-making. Instead of optimising isolated steps, AI will understand the full flow – predicting bottlenecks before they occur, identifying exceptions that matter, and orchestrating recovery plans grounded in financial and service-level impact. This closes the gap between planning and execution.

AI can’t drive business value without understanding how your business flows. When you give it that context – the real-time visibility into how work gets done – the trust comes naturally. You see why it made a decision and how to make it better. That’s when AI becomes enterprise-ready.”

Baris Gultekin, Vice President of AI, Snowflake

Data becomes a more powerful moat for Enterprise AI

“The pace of innovation in frontier AI models has provided the enterprise with an incredibly powerful and mature foundation. Give or take a few benchmarks, model capabilities are reaching a high floor, offering similar, state-of-the-art performance. Similarly, as building AI-powered apps becomes faster and easier to build for people of all technical backgrounds, the features that distinguish one product from another will also begin to fade. 

By 2026, we’ll see this commoditisation accelerate across the entire AI stack. In this new landscape, an organisations’ sustainable competitive advantage won’t be the model or application itself, but the unique, proprietary data an organisation holds and its ability to reason over it. The companies that master the ‘data flywheel’ – using their unique data to create better AI, which in turn generates more unique data – will establish meaningful differentiation for years to come, and continue to benefit from improvements to the AI tools themselves.”

Agent Interoperability will unlock the next wave of AI productivity

“Today, most AI agents operate in walled gardens, unable to communicate or collaborate with agents from other platforms. This is about to change. By 2026, the next major frontier in enterprise AI will be interoperability – the development of open standards and protocols that allow disparate AI agents to speak to one another. Just as the API economy connected different software services, an ‘agent economy’ will quickly emerge, where agents from different platforms can autonomously discover, negotiate, and exchange services with one another. Solving this challenge will unlock compound efficiencies and automate complex, multi-platform workflows that are impossible today to usher in the next massive wave of AI-driven productivity.”

Dwarak Rajagopal, Vice President of AI Engineering and Research, Snowflake

The future of AI agents is in self-verification, not human intervention

“In 2026, the biggest obstacle to scaling AI agents – the build-up of errors in multi-step workflows – will be solved by self-verification. Instead of relying on human oversight for every step, AI will be equipped with internal feedback loops, allowing them to autonomously verify the accuracy of their own work and correct mistakes. This shift to self-aware, ‘auto-judging’ agents will enable the development of complex, multi-hop workflows that are both reliable and scalable, moving them from a promising concept to a viable enterprise solution.” 

Mike Blandina, Chief Information Officer, Snowflake

AI will redefine the role of the CIO from IT Operations to Enterprise Innovation

“In the next year, the role of the CIO will shift from ‘IT’ to ‘ET’ – from information technology to enterprise technology leadership. Traditional metrics like ticket counts will still matter, but forward-looking CIOs will adopt a solution mindset. The modern CIO must leverage AI not just to source tools, but to engineer outcomes. Instead of recommending SaaS vendors, CIOs will assemble multiple LLMs to build solutions to solve today’s problems while anticipating what’s next. The IT function will no longer be just about infrastructure – it will be about delivering corporate intelligence with AI-driven solutions and providing leverage across every critical business platform. AI will redefine the CIO as a business innovator, not just a technology operator.”

CIOs will become an organisation’s number one sustainability steward

“In 2026, CIOs will be expected to own the responsibility for tech-driven sustainability. As enterprises face mounting pressure from regulators, investors, and customers to meet climate goals, CIOs will be expected to deliver the data, platforms, and AI-driven insights that make sustainability measurable and actionable. From optimising cloud workloads for lower energy use to applying advanced analytics that cut supply chain emissions, CIOs will increasingly be at the centre of corporate sustainability strategies. This isn’t just about compliance reporting, it’s about leveraging technology to transform sustainability into a source of efficiency, growth, and differentiation for the enterprise.”

  • Data & AI
  • Digital Strategy