Top 10 Digital Transformation Strategies [2026]: A Data-Driven Guide for Future-Ready Leadership

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Executive Summary: Top Digital Transformation Strategies

Top 10 Digital Transformation Strategies Across Sectors

1. Artificial Intelligence (AI) Integration & Advanced Analytics: 78% of enterprises will use AI in at least one business function this year. The global AI spending is projected to reach USD 632 billion by 2028.
2. Cloud Modernization & Legacy Transformation: Worldwide public-cloud spending will reach USD 723.4 billion in 2025. Nearly 85% of enterprises will adopt a cloud-first model for driving agility and reducing time-to-market.
3. Digital Upskilling and Workforce Transformation: The World Economic Forum (WEF) projects 59% of workers will require reskilling by 2030, with 39% of existing skills becoming obsolete. Employees with AI expertise earn a 56% wage premium.
4. Data Governance & Data-Driven Decision-Making: The global data governance market will reach USD 22.87 billion by 2032 at a compound annual growth rate (CAGR) of 21.95%. Yet, only 25% of companies base nearly all strategic decisions on data.
5. Customer Experience (CX) Reinvention: The CX management market will expand from USD 22.35 billion in 2025 to USD 68.24 billion by 2032. Companies improving CX scores by just one point are able to earn USD 1 billion+ in added annual revenue.
6. Process Automation & Hyperautomation: The global hyperautomation market will surge from USD 65.67 billion in 2025 to USD 270.63 billion by 2034. Despite this, only 1% of enterprises have achieved mature end-to-end automation across workflows.
7. Cybersecurity & Digital Trust: Global cybercrime damages are forecast to reach USD 10.5 trillion annually by 2025. About 81% of organizations plan to adopt zero-trust frameworks by 2026. Still, only around 2% report full capability across all cyber resilience areas.
8. Digital Ecosystems & Partnerships: Salesforce and its partners are expected to create USD 1.6 trillion in new revenue and 9.3 million jobs by 2026. For every USD 1 spent on Google Cloud, partners earn up to USD 7.05 in services revenue.
9. Innovation Culture & Agile Leadership: Companies with agile leadership outperform peers by 25% and respond five times faster to market shifts. Agile adoption among developers climbed from 37% in 2020 to 86% in 2025.
10. Sustainability & Green IT Transformation: The International Energy Agency (IEA) projects global data center electricity consumption will more than double to 945 TWh by 2030. McKinsey projects data center capex to reach USD 6.7-7 trillion by 2030.

Case Studies and Measurable Outcomes

• Domino’s: Generates 85% of US sales through digital channels, demonstrating a measurable link between digital investments and revenue growth.
• Nike: DTC business reached USD 44.5 billion of total sales, supported by its app-based membership ecosystem of over 150 million users.
• Microsoft: Cloud pivot lifted revenue 22% year-on-year to USD 95 billion, driving sustained double-digit growth in its Intelligent Cloud segment.
• Novartis: AI-driven R&D platform reduced data-processing time by 20%, highlighting ROI and accelerated clinical insight generation through multi-cloud analytics.

You may also like:

• Digital Transformation Roadmap 2026
• Top Digital Transformation Technologies to Watch
• Digital Economy Trends 2026

How We Researched and Where This Data is From

• Analyzed our 3100+ industry reports on innovations to gather relevant insights and create a master digital strategy matrix. Cross-checked this information with external sources for accuracy.
• Leveraged the StartUs Insights Discovery Platform, an AI- and Big Data-powered innovation intelligence platform covering 9M+ emerging companies and over 20K+ technology trends worldwide, to confirm our findings using the trend analysis tool.

Frequently Asked Questions (FAQs)

1. How large will the digital transformation market be by 2026?

According to Markets and Markets, the digital transformation market size is growing from USD 1107.06 billion in 2025 to USD 1864.94 billion by 2031 at a CAGR of 9.1%.

2. Are most companies already pursuing digital transformation?

Yes. About 89% of companies have adopted or plan to adopt a digital-first strategy.

Top 10 Digital Transformation Strategies Across Sectors

G2 reports that 94% of enterprise organizations use cloud computing. However, only 30% of broader digital transformation initiatives hit their intended goals. This shows the execution gap many organizations still face.

This article examines 10 high-impact digital transformation strategies and also offers valuable insights, real-world case studies, and actionable frameworks to support strategic decisions for business leaders.

1. AI Integration and Advanced Analytics

According to a 2025 McKinsey report, 78% of enterprises now use AI in at least one business function, up from 72% in an earlier survey.

Yet, more than 80% of respondents say their organizations are not seeing a tangible impact on enterprise-level EBIT from their use of generative AI.

On the spending side, IDC projects global AI outlays to reach USD 632 billion by 2028, with US AI spending at USD 336 billion and generative AI at USD 108 billion by 2028.

Enterprise application roadmaps are also shifting. 40% of enterprise apps will feature task-specific AI agents by 2026. And over 50% of enterprises will use AI security platforms by 2028.

Meanwhile, edge spending hits USD 261 billion in 2025 and USD 380 billion by 2028. This market growth reflects demand for low-latency AI at the device and plant floor.

Moreover, Deloitte’s 2025 tech value survey finds 74% of respondents invested in AI and GenAI in the past year. Also, PwC notes that around half of CEOs expect generative AI to improve profitability and that many reallocate ~10% of financial and human resources between projects year-on-year.

However, F5 reports that only 2% of enterprises are fully prepared to capture AI benefits, even as 25% of applications already embed AI. This data highlights the need for security controls (AI firewalls, data labeling) and model-risk governance to protect value.

Therefore, organizations must move beyond AI adoption and focus on operationalizing it by embedding analytics, defining metrics, and restructuring workflows. They should also strengthen data governance and security. Organizations should track outcomes such as cost per transaction, forecast accuracy improvements, and incremental revenue from AI-driven services.

2. Cloud Modernization and Legacy System Transformation

Gartner forecasts that worldwide end-user spending on public cloud services is expected to reach USD 723.4 billion in 2025, rising from USD 595.7 billion in 2024. The market size reflects a growth rate of 21.5% in 2025.

Further, the market for cloud modernization services, including migration, refactoring, and optimization of legacy workloads, will reach USD 969 million by 2031, exhibiting a CAGR of 7.4%.

Rising pressure on organizations to offer agility, scalability, and cost-efficiency through modern infrastructure drives this trend. Gartner analysts predict that more than 85% of organizations will adopt a cloud-first approach by 2025. They add that companies will struggle to execute their digital strategies without leveraging cloud-native architectures and technologies. This transition allows business leaders to deploy new digital services faster, respond quickly to market changes, and shorten time-to-value for IT investments.

In practice, organizations refactor applications for cloud platforms and adopt containerization and microservices to enable faster release cycles. For example, in 2025, Rakuten Mobile migrated telecom network functions into microservices-based clusters for a cloud-native rollout.

Also, organizations are shifting away from single-cloud dependencies to improve flexibility and reduce risk. A recent estimate shows that nearly 76% of enterprises now use two or more cloud providers.

The multi-cloud strategy lowers infrastructure ownership costs, strengthens system resilience, accelerates innovation cycles, and enables smooth integration of emerging technologies like AI and the Internet of Things (IoT) into core operations.

However, effective execution of a cloud modernization strategy requires a structured operational approach. Organizations must define cloud service governance, build cloud-native development skills, and track metrics such as mean time to deploy, cost per workload, and application performance improvements.

3. Digital Upskilling and Workforce Transformation

The WEF estimates that by 2030, nearly 59% of workers will require reskilling. Workers should expect that 39% of their existing skill sets will change or become outdated between 2025 and 2030.

Meanwhile, the PwC reports that workers in AI-exposed industries experience 66% faster skill change than those in other sectors. It also finds that employees with AI skills earn a 56% wage premium compared to peers in similar roles without AI capabilities.

These data reflect key drivers such as the rapid adoption of artificial intelligence, cloud-native workflows, and Industry 4.0 requirements, which compel organizations to reskill their workforces at scale. According to a survey cited by S&P Global, nearly nine out of ten businesses say they will need to access, acquire, or develop new technology skills in 2025.

Organizations that invest in workforce transformation achieve higher productivity, accelerate time-to-value, and improve talent retention. Manufacturers report that 94% of firms retain existing headcount by upskilling workers through smart manufacturing technologies instead of replacing them.

Additionally, a LinkedIn report states that companies that deploy personalized learning journeys, manager-led growth dialogues, and internal mobility programs achieve stronger workforce outcomes. They also record significantly higher internal promotion rates and talent retention.

However, the market still faces structural challenges. Many organizations invest in training but fail to link skill development to measurable business outcomes or to integrate new capabilities into workflows. For example, although many companies plan to reskill, only 22.4% of HR professionals say their organizations plan to prioritize skill development over the next two years.

Therefore, business leaders must map future-state skills to measurable business outcomes, such as the percentage of the workforce certified in AI/ML or digital literacy levels. They should embed continuous learning into everyday operations to ensure agility and relevance.

Also, they need to track metrics like internal mobility, skills-gap reduction, and talent productivity while using platforms that align workforce capacity with emerging business priorities.

4. Data Governance and Data-Driven Decision Making

The data governance market is projected to grow to USD 22.87 billion by 2032, representing a CAGR of around 21.95%.

At the same time, surveys show that only 25% of organizations base nearly all strategic decisions on data. Around 44% make most of their key decisions data-driven.

In 2025 and beyond, rising data volumes from IoT devices and growing real-time analytics demands drive this trend. Regulatory pressures on data transparency and AI governance further push organizations to convert raw data into actionable insights.

A recent review of data-governance trends found that organizations must adopt real-time governance and monitor streaming data. They must also integrate governance with corporate reporting to satisfy investor and regulatory demands.

Further, by 2026, new data governance best practices will shift from being a compliance afterthought to a strategic differentiator. A TDWI study found that 36% of data leaders view data governance as a key priority to improving an organization’s success with business intelligence (BI) and analytics.

From the decision-making side, organizations are shifting from intuition-based to data-driven frameworks. A 2025 OECD analysis highlights this shift, noting a clear move away from evidence-informed decision-making toward fully data-driven approaches. Also, 52% of organizations now identify compliance and regulatory readiness, including data governance for AI, as their biggest adoption challenge.

In practical terms, organizations must define governance frameworks that establish clear roles, policies, and accountability structures. They also need to ensure data quality and integrity while adopting metadata management and lineage tracking systems.

Additionally, they should integrate analytics platforms with governance controls and monitor key metrics, including the percentage of decisions supported by analytics, data quality scores, time to insight, and regulatory compliance incidents.

For instance, AXIS Capital, a global specialty insurer, implemented a structured governance framework to standardize critical reference data such as underwriting and rating codes, ensuring consistent and trusted data across product lines and geographies.

5. Customer Experience (CX) Reinvention

By 2025, about 89% of businesses plan to compete primarily on customer experience (CX) instead of relying solely on price or product. A survey referenced by Salesforce found that 80% of customers say the experience a company provides is as important as its products and services.

The global customer experience management (CEM) market is projected to grow from USD 22.35 billion in 2025 to USD 68.24 billion by 2032. This growth highlights how businesses are investing in CX platforms, analytics, and orchestration tools.

Meanwhile, firms report rising expectations from consumers. For example, a study by Salsify found that 49% of respondents said they prefer a mix of online and in-store shopping.

The key drivers of CX reinvention include rapid adoption of AI-powered personalization, with 82% of executives planning customer-experience initiatives that include AI in 2025. Also, the rise of unified data platforms, that 90% of businesses will rely on unified data platforms to deliver digital CX by 2025.

Another key driver is the acceleration of self-service. For example, Gartner predicts that by 2025, 80% of customer service and support organizations will be applying generative AI technology in some form to improve agent productivity and customer experience (CX).

Additionally, generative AI chatbots, sentiment analytics engines, real-time personalization platforms, unified customer data platforms (CDPs), omnichannel orchestration fabrics, and immersive technologies such as AR/VR for experiential engagement. These tools encourage organizations to deliver highly responsive, personalized, and smooth customer experiences at scale.

Companies that raise their CX scores by just one point can generate over USD 1 billion in additional revenue. They achieve this through higher customer loyalty, 15-25% higher cross-sell rates, and 5-10% greater wallet share. On the flip side, poor experiences are costly. More than 50% of customers will abandon a brand after a single negative interaction.

However, many organizations struggle to operationalize CX transformation. Challenges include data silos, under-investment in human+AI hybrid models, and misalignment between CX investments and business outcomes. For example, 79% of customers expect consistent interactions across departments. Yet, 55% say they usually communicate with separate departments instead of one unified company.

6. Process Automation and Hyperautomation

The global hyperautomation market is expected to grow to USD 65.67 billion in 2025, and is projected to reach USD 270.63 billion by 2034, at a CAGR of about 17.0%. In parallel, the broader industrial automation and control systems market is estimated to hit USD 226.8 billion in 2025 with a projected 10.8% CAGR through 2030.

Meanwhile, Gartner forecasts that by 2026, 30% of enterprises will automate more than half of their network activities, up from less than 10% in mid-2023, showing a rapid rise in operational automation.

According to the 2025 report from McKinsey & Company, over 92% of companies plan to increase their investments in AI over the next three years, which is a key enabler for hyperautomation.

Robotic process automation (RPA), AI, and ML for decision-making, process, and task mining are driving process automation and hyperautomation. Intelligent document processing, orchestration platforms that connect bots and humans, and real-time analytics further enhance automation by dynamically adjusting triggers. For example, the Options Clearing Corporation (OCC) implemented a hyper-automation platform across its legal department for regulatory filing, corporate actions, and new product development.

Also, Omega Healthcare Management Services automated administrative tasks such as billing and document processing for 60-70% of its clients. The automation saved more than 15K employee hours per month, reduced documentation time by 40%, and cut turnaround time by 50%. It also achieved 99.5% accuracy, generating an estimated 30% return on investment (ROI).

Moreover, process and task mining are projected to grow at a 28.74% CAGR within the hyperautomation market by 2030.

Despite high investment intent, only about 1% of firms call themselves mature in embedding AI and automation end-to-end in workflows.

Therefore, business leaders should map existing processes to identify automation opportunities and prioritize orchestration frameworks that integrate RPA, AI, and human workflows. They should also define clear outcomes and refine automation initiatives through continuous iteration.

7. Cybersecurity and Digital Trust

The global cybercrime damages are projected to hit USD 10.5 trillion annually by 2025. In parallel, the 2025 PwC survey of 4042 executives across 77 countries found that cyber risk now outranks both digital and technology risk as the top concern for organizations.

Moreover, CrowdStrike reported that 79% of detections were malware-free, showing a shift toward stealthier attacks and a 150% rise in China-linked adversary activity.

Meanwhile, no sector achieved over 50% high-trust ratings among consumers, with trust overall either stagnating or declining.

About 81% of organizations plan to adopt a zero-trust framework by 2026, according to Gartner. They are moving away from traditional perimeter-based security to strengthen access controls and protect distributed digital environments. Security researchers disclosed over 30K vulnerabilities in the past year, a 17% increase that indicates the rapidly expanding attack surface.

However, PwC found that only around 2% of organizations claim to have full capability across all critical cyber resilience areas.

To operationalize this strategy, business leaders must embed cybersecurity and digital trust into every phase of their transformation roadmap. They should focus on high-risk areas such as cloud, AI, supply chains, and machine identities while adopting frameworks like Zero Trust and identity-centric security.

Additionally, they need to define and track metrics such as time to detect, breach cost reduction, percentage of secure digital services, and trust indicators like consumer trust ratings or third-party assurance scores.

For example, Accenture adopted a security-first approach for its cloud transition by embedding identity-centric and zero-trust principles from the start of its hybrid and multi-cloud journey. The company further defined measurable outcomes, such as running over 1 billion+ events per day across 624K employees and achieving 91% native cloud security controls with automated prevention.

Likewise, governance must span board-level oversight, executive engagement, and cross-functional collaboration, especially between the C-suite and the security function.

8. Digital Ecosystems and Partnerships

Ecosystems now drive top-line growth rather than serving as side channels. The AWS Partner Network (APN) counts more than 130K partners across 200+ countries, with about 70% headquartered outside the USA.

SAP reports 25K+ partners in its PartnerEdge/open ecosystem, which reflects how cloud ERP and AI roadmaps increasingly ride multi-party delivery.

Moreover, Salesforce’s AppExchange expanded to around 6000 apps, demonstrating sustained independent software vendor (ISV) innovation built around its core platform.

Ecosystem economics continue to strengthen. Canalys research cited by Google Cloud shows that for every USD 1 customers spend on Google Cloud, partners are able to earn up to USD 7.05 in incremental services revenue over three years. This return reflects the advantage partners gain when they support customers across the full lifecycle.

Additionally, IDC predicts that Salesforce and its partners will generate USD 1.6 trillion in new business revenues and 9.3 million jobs by 2026. They also estimate that the partner ecosystem will be nearly six times the size of Salesforce itself by 2026.

In capital markets, Euroclear and Microsoft signed a seven-year deal to modernize core market infrastructure using cloud, generative AI, and analytics. The partnership aims to build a secure financial data-sharing ecosystem and embed AI-powered insights into Euroclear’s FundsPlace platform.

Microsoft also invested in Veeam on February 25, 2025, to co-develop AI-enhanced data-resilience products on Azure, indicating cyber-recovery as a joint value pool.

In data and AI platforms, Snowflake expanded its partner network to around 12K partners after its 2025 revamp. The company aligned co-innovation and early product access to accelerate customer outcomes.

Likewise, Google Cloud reports having thousands of partner-built agents within the Gemini Enterprise AI agent ecosystem. The company validates these agents for quality and security.

APN’s scale enables vertical solution packs combining independent software vendors (ISVs), system integrators (SIs), and hyperscalers. Many enterprises now treat these collaborations as the default path to AI, data, and application modernization.

These partnerships demonstrate how well-structured ecosystems translate collaborative innovation into durable competitive advantage and accelerated digital transformation.

9. Innovation Culture and Agile Leadership

McKinsey & Company reports that companies with highly agile leadership teams outperform peers by 25% during uncertain times. These teams also respond up to five times faster to market changes.

Meanwhile, Deloitte’s 2025 report notes that 85% of organizations say they need to create more agile ways of organizing work to swiftly adapt to market changes.

Also, the report shows that agile principles are spreading into marketing, customer service, and operations. This expansion highlights how iterative workflows and continuous feedback loops now drive enterprise innovation.

In 2025, agile adoption among developers reached 86%, rising from about 37% five years earlier. Teams using agile practices report up to 47% higher productivity and 40% better project visibility.

Moreover, Schneider Electric expanded its leadership in the digital age program to all business leaders globally. The initiative focused on AI literacy, data-driven decision-making, and encouraging autonomy in regional units. It also reported an increase in locally initiated digitization projects and shorter innovation cycles.

To operationalize this strategy, organizations must build a culture of continuous learning. Korn Ferry’s report highlights learning agility and tech-savvy leadership as key differentiators for growth-oriented firms. Leaders in India (85%) and the UAE (82%) express strong confidence that emerging technologies will enhance their company’s value.

Further, business leaders must encourage teams to test, fail fast, and iterate by granting autonomy. They should track innovation through metrics such as revenue share from new initiatives, experiments per quarter, and idea-to-launch lead time.

Importantly, organizations align leadership behaviors with agile values by encouraging transparency, cross-functional collaboration, psychological safety, and rapid decision-making.

10. Sustainability and Green IT Transformation

The International Energy Agency (IEA) projects that global data center electricity consumption will more than double to around 945 TWh by 2030. AI-optimized facilities are expected to quadruple their energy demand, putting additional pressure on power grids, water resources, and emissions targets.

At the same time, capital continues to flow into a cleaner energy supply. BloombergNEF reports a record USD 386 billion invested in new renewables in 1H 2025. Also, REN21 notes that 741 GW of renewable power was added in 2024-2025, which is the largest annual increase on record.

Moreover, the European Union enforces the Corporate Sustainability Reporting Directive (CSRD) starting in 2025. It mandates large and listed firms to provide detailed climate disclosures, including Scope 3 emissions.

Operational efficiency gains remain uneven across the industry. Uptime Institute’s survey reports an average power usage effectiveness (PUE) of around 1.5 for the sixth consecutive year. In contrast, Google’s data center fleet achieved a PUE of 1.09, highlighting the advantage of advanced cooling and infrastructure upgrades.

Additionally, Google and Fervo expanded their 2023 pilot into an approved 115 MW (approx.) 24/7 enhanced geothermal project for Nevada data centers in 2025. The initiative establishes a model for firm, carbon-free baseload energy in digital infrastructure.

Google also entered into a deal with Kairos Power and the Tennessee Valley Authority (TVA) to site an advanced small modular reactor (SMR) in Tennessee (Oak Ridge) that is expected to start operations around 2030.

Likewise, Microsoft advanced several zero-carbon initiatives, including a 20-year, 835 MW nuclear supply agreement tied to the Three Mile Island restart scheduled for 2028. It also began collaborating on nuclear and fusion projects, with construction of the Helion fusion plant starting in July 2025.

AWS also matched 100% of its electricity consumption with renewable energy in 2023. By January 2025, it had added 2.5 GW of new renewable projects across Europe.

Meanwhile, McKinsey projects that global data center capital expenditure (capex) will reach about USD 6.7-7 trillion by 2030.

Case Studies: Examples of Successful Digital Transformation

Domino’s Pizza – “A Tech Company That Happens to Sell Pizza”

As of 2023, Domino’s reported that more than 85% of US retail sales came via digital ordering channels, marking digital as the dominant route for revenue. The company’s 2024 annual report shows global retail sales of ~USD 4.7 billion and global retail sales growth of +5.9% for fiscal 2024.

Moreover, annual ICT spending by Domino’s was estimated at USD 225.3 million in 2024 according to a GlobalData case study, illustrating the material investment in technology.

Digital ordering channels account for more than 65% of US sales across mobile apps, smart devices, and smart assistants, reflecting broad multi-channel deployment.

In Q2 2025, the company reported a 4.3% year-on-year revenue increase, driven by higher order volumes and pricing actions. This performance supports how digital investments directly contribute to operational growth.

Key Takeaways for Business Leaders

• Make digital channels the default revenue path, not an afterthought. Set targets (e.g., % of sales via digital) and monitor outcomes.
• Align technology spend (ICT budget) with business targets (growth, margin lift) and measure return (e.g., digital contribution to sales).
• Use multi-channel ordering and real-time data to improve customer experience and scalability.
• Scale transformation by embedding analytics, operations, and technology in the business model.

Nike – Direct-to-Consumer (DTC) Digital Pivot

In a 2023 analysis, Nike reported that its direct-to-consumer (DTC) channels generated approximately USD 44.5 billion. This accounted for nearly 39% of total sales, marking a major shift from when wholesale once represented about 84% of its model.

Moreover, Nike set a strategic goal during its consumer direct acceleration phase to surpass a 30% digital penetration target ahead of schedule. It is targeted to eventually reach nearly a 50% digital share over time.

Despite these ambitions, in Q2 2025 the company reported a 13% year-on-year decline in its Nike Direct digital business, and wholesale sales dropped by 3%. Consequently, quarterly revenue reached USD 12.4 billion, highlighting the challenge of sustaining high-growth DTC momentum.

The pivot to DTC also emphasized building member ecosystems and strengthening data capture. For instance, Nike’s app-based membership reportedly surpassed 150 million members, allowing the company to improve personalization and direct engagement.

Additionally, Nike reduced its reliance on third-party distribution by exiting a major online retailer’s platform in 2019. It renewed the collaboration in 2025, reflecting the company’s evolving channel strategy.

Key Takeaways for Executives Building Digital Transformation Strategies

• Set ambitious but measured targets and track actuals versus goals to maintain strategic alignment.
• Transition distribution models strategically, not merely shifting to digital first but rethinking partner ecosystems, data ownership, and customer access.
• Invest in owned platforms and member ecosystems to build customer data assets.
• Monitor early signs like digital business growth deceleration and remain ready to recalibrate strategic assumptions and operating model choices.
• Recognize that digital transformation is about designing how the business model, channels, data, and operations change together.

Microsoft – Culture and Cloud Transformation

Microsoft shifted to a cloud-first, AI-first model. In fiscal year 2024, its intelligent cloud segment delivered revenue growth of approximately 20% year-on-year, highlighting the business impact of its cloud pivot.

In 2024, Microsoft’s market capitalization surpassed USD 3 trillion, demonstrating strong investor confidence in its digital transformation strategy. The company reports that over 85% of Fortune 500 organizations use Microsoft AI solutions, indicating the scale and enterprise adoption of its platform strategy.

Internally, Microsoft focused on improving its culture by shifting from a know-it-all to a learn-it-all mindset among its 220K employees. This shift formed a key part of its broader workforce strategy to strengthen digital dexterity.

Moreover, Microsoft’s internal cloud migration delivered annual savings of about USD 500 million in data center infrastructure and operational costs. The company achieved this reduction through large-scale consolidation and cloud re-platforming.

Further, Microsoft states that its ecosystem includes more than 1000 customer transformation stories. IDC estimates that AI and related cloud services will generate a global cumulative impact of USD 22.3 trillion by 2030.

Key Takeaways for Executives Building Digital Transformation Strategies

• Align technology transformation, whether cloud or platform, with business model evolution to redefine how you deliver value and generate revenue.
• Invest in culture and talent transformation alongside technology to ensure workforce and mindset shifts that enable true scale.
• Set and transparently track quantitative targets such as cloud revenue, subscription growth, and cost savings within your strategy roadmap.
• Build or partner for a platform and ecosystem approach to create value beyond your organization and harness collective network effects.
• Leverage internal transformation to validate external solutions by migrating your own systems to new platforms, gaining credibility, insights, and cost efficiencies simultaneously.

Novartis – Data-First R&D Modernization

Novartis reports that it is integrating AI and data science across its R&D activities to accelerate drug design and clinical trial processes. The company is targeting more than 15 submission-enabling readouts over the next two years and maintains a pipeline of over 30 potential high-value medicines. In 2024, it reached approximately 300 million patients with its therapies.

Moreover, Novartis’ multi-cloud analytics platform ingests and unifies about 9 TB of data from more than 80 sources across development, commercial, manufacturing and quality, and corporate functions. It processes data roughly 20% faster than legacy systems and enables quicker and more informed decisions.

Also, the internal data42 program onboarded more than 2000 clinical studies and tested a dozen ML models to generate insights for development decisions. This effort showcases the breadth of the company’s analysis-ready clinical data repository.

Novartis presented AI approaches at NeurIPS and ICLR to predict novel molecules and targets with a higher probability of disease modification. These efforts show that algorithmic discovery has advanced beyond pilot phases and has become integral to the scientific workflow.

Further, in 2024, Novartis signed a multi-target collaboration worth up to USD 1 billion with Generate:Biomedicines to apply generative AI to protein therapeutics. This partnership demonstrates the company’s belief that algorithmic design can shorten preclinical timelines.

Key Takeaways for Business Leaders

• Quantify sources, latency, and throughput, and operate analytics as a shared service across R&D, manufacturing, and commercial functions.
• Extend AI applications beyond discovery into clinical operations and manufacturing, where predictive maintenance, document intelligence, and feasibility models accelerate time-to-value.
• Embed model lineage, access controls, and privacy techniques to ensure scaled AI systems pass audits and maintain momentum beyond pilot phases.
• Form strategic alliances to enhance internal capabilities and accelerate pipeline milestones; treat ecosystem design as a core strategy.

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