Cloud for CEOs:

The most successful organizations are disrupting their competitors and entering new markets by innovating more quickly and efficiently. To be truly innovative as an enterprise, let alone become a digital or generative AI disruptor, businesses need to get out of the building, understand their customer needs, and respond faster than ever based on data and anecdotes. An enterprise’s ability to innovate isn’t about technology adoption, it’s about the right combination of people, processes and technology, and being an innovative CEO requires overcoming organizational challenges in four areas: culture, skills, organization and data. Get these right, and you will be able to truly leverage technologies such as cloud computing, machine learning and generative AI to innovate at scale.

When it comes to disruption in business, experts suggest the experience of being disrupted is hard to detect. “We studied 3,600 companies. Famous cases of companies or industries completely going away because of disruption are actually quite rare,” said Omar Abbosh, CEO of Accenture’s Media and Technology business. “Much more common is what we call compressive disruption; where the profit streams of companies become squeezed over time…. And that’s a giant problem because it actually feels normal.”

As much as CEOs fear disruptors cropping up in their industry, concern is better placed on the readiness of their organization to respond to changing customer expectations driven by new experiences created outside their core industry. We see three levels of innovation helping companies move forward and stay competitive:

1. incrementally better services (the table stakes),
2. new gap-filling value creators (addressing pain in the market),
3. and completely new customer experiences through the use of new technologies (unexpected offerings), which can lead to new business models.

These are the kinds of innovations that grant enterprises sustainable advantages, market share, and customer loyalty. In every case, your company’s time to value and time to experiment are the key metrics that predicts business success.

For many companies, the term "digital transformation" has become synonymous with technology updates such as moving to the cloud. What often does not happen is a true business transformation that makes a significant difference to customers.

For CEOs, this means recognizing that digital transformation is not just a technology upgrade, but a strategic initiative to grow the business and outperform competition. Driving growth means leveraging technology to increase revenue, enter new markets, and improve the customer experience through innovative products and services in areas such as IoT, social commerce, or generative AI. At the same time, achieving competitive advantage requires using advanced tools to improve operational efficiency, make data-driven decisions, and respond quickly to market changes. By focusing on these dual goals, CEOs can ensure that they not only keep pace with industry advancements, but also set the stage for sustained success and market leadership.

To go through a digital transformation, you need to support a lot of innovation, and much of it is software-driven . The pace of development for physical products is relatively slow, so existing development processes tend to be slow. If you run your software innovation in the same traditional model as a physical product innovation cycle, you will be left behind. The digital transformation winners have innovated quickly to personalize customer experiences, harness customer analytics, manage new direct channels to their customers, and embrace fast changes. They’ve used cloud computing to support a huge increase in the scale and global reach of their operations. They have their critical enterprise data in the cloud, enabling them to rapidly build enterprise-grade generative AI applications.

The entrenched values, behaviors, and norms of organizational culture can be significant barriers to the digital transformation necessary to innovate. This resistance comes from a fear of the unknown, a preference for maintaining established processes, and a lack of digital and data literacy among employees. When the organizational culture is rigid and averse to change, it hinders innovation and adaptation, making it difficult to effectively implement digital initiatives. This cultural inertia leads to missed opportunities, reduced competitiveness, and failure to meet evolving customer expectations in an increasingly digital marketplace. Therefore, addressing cultural barriers is critical for organizations seeking to thrive in the digital age, as it enables smoother transitions, fosters a mindset of continuous improvement, and unlocks the full potential of digital tools to drive business success.

Skills shortages block technology adoption. As the pace of technologic advancement increases, it’s not practical to think of skills as fixed assets that are acquired as part of building a project team based on a specific technology. Technology skills are continuously developed by teams of developers exploring new technologies as they emerge and mature. Leaders should foster a “learning organization” culture, where new ideas are explored and shared as a matter of course. To make the learning culture work, leaders offer incentives that encourage staff to learn new skills and remain with the organization as they become more experienced. With the rapid advancement of generative AI, possessing skills in this area has become particularly valuable. These include understanding AI model training, data manipulation, and deployment of AI-driven solutions. A realistic approach might be to have a skills incentive program where specific in-demand technologies, such as generative AI, are tied to ongoing bonuses for people who have or acquire those skills.

According to Accenture* 94% of C-suite executives say their operating model puts their organization's growth and performance at risk. As a consequence, leading organizations have switched from traditional project teams to small and cross-functional product teams in their digital organizations. This is a critical change that reflects the new reality of business: products must continually evolve to stay relevant.

The job of a development team is to be responsible for continuous improvement of their product. There’s no technical reason why software services can’t be updated many times a day. In traditional organizations, it takes too long to hand over products from development teams to (often outsourced) operations teams. DevOps is an organizational model where product teams build, and then run what they build. Amazon CTO Werner Vogels calls this “run what you wrote.” In most enterprises, there is separation between the business and the development organization, which isn’t present in digital organizations. For example, each team at Amazon Web Services (AWS) owns their own roadmap, develops their own service, and operates it. They are given headcount, budget, and growth goals, and they operate as a relatively self-contained unit. These are fairly small, co-located “two pizza teams.” Groups of closely related teams report to a general manager, who owns the combined product roadmap, development and operations, allocates resources and creates new teams as needed. . An additional benefit of product-based teams is that they naturally manage their own technical debt rather than accumulating it, and they don’t create the kind of operational lock-in that occurs when a project is delivered by a team that moves on immediately to other projects.

Data and data-driven decision making can be an obstacle to digital transformation if organizations lack the data literacy and infrastructure to effectively use their data. Without a strong foundation in data literacy, employees may struggle to interpret data correctly and make informed decisions, leading to distrust in data-driven strategies. This becomes even more critical in the context of generative AI, where data quality and understanding are paramount. Generative AI-natives that are adept at using advanced data techniques can leapfrog traditional organizations by rapidly developing innovative solutions and use cases. If an organization fails to cultivate data literacy and integrate data-driven decision-making into its culture, it risks falling behind competitors, missing out on the transformative potential of generative AI, and ultimately losing its competitive edge in a data-centric business environment. As a result, improving data literacy and fostering a culture that embraces data-driven insights are essential to unlocking the full power of digital transformation and generative AI technologies.

Adopting a cloud-first strategy is critical for organizations looking to remain agile and scalable in today's fast-paced business environment. By leveraging cloud services, organizations can quickly build, deploy, and manage applications and AI models, handle massive amounts of data, and support real-time analytics without the constraints of traditional on-premises infrastructure. By leveraging cloud-native services, organizations have access to cutting-edge tools for developing, training, and deploying generative AI models. This not only speeds time to market for innovative solutions, but also ensures that the business can efficiently scale globally to meet growing demand and new opportunities.

Integrating AI-powered analytics through cloud-based tools is transforming the way organizations make decisions. By harnessing the power of generative AI, companies can extract actionable insights from their data, predict market trends, optimize supply chains, and deliver personalized customer experiences. The cloud's ability to process and analyze data in real time enables businesses to respond quickly to changes in the market, customer behavior, and operational dynamics. This real-time data processing ensures that decisions are based on the most current and relevant information, giving the company a significant competitive advantage in a dynamic marketplace.

To truly reap the benefits of cloud and AI technologies, it is essential to foster a culture of continuous innovation and learning. Organizations must encourage a learning mindset where employees are motivated to explore and experiment with new technologies. Providing comprehensive training and resources helps develop expertise in cloud computing and generative AI, and empowers teams to drive innovation from within. Implementing incentive programs that reward employees for contributing innovative ideas and successfully deploying AI-based solutions can further cultivate this culture. Encouraging cross-functional collaboration ensures that different perspectives are considered, leading to more robust and creative solutions. By embedding these practices into the organizational fabric, companies can sustain long-term innovation and adaptability.

There are many changes needed to navigate a digital transformation or cloud migration and to adopt new technologies in general, but the most important success factor is that rapid innovation is enabled by making change in many small increments, in a product-based organization that focuses on reducing time to value.

* COVID-19: Busting the myths of agile transformation