Four Practices Your Organization May Need to Lead Its AI Transformation

Four Practices Your Organization May Need to Lead Its AI Transformation

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Four Practices Your Organization May Need to Lead Its AI Transformation

Even as the pandemic has accelerated transformation in many aspects of business, artificial intelligence (AI) has advanced over the past two years with notable speed.

As more leaders recognize and rely on AI’s utility in uncovering and scaling data-driven insights and freeing their workforce to solve problems with creativity, they increasingly see AI technologies and processes creating value for employees, partners, and customers.

Though we are still in the early days of AI transformation, organizations are rapidly developing and scaling their capabilities. A survey of 2,875 executives for Deloitte’s most recent State of AI in the Enterprise report found that market-leading AI-driven organizations primarily focus on leading practices in four key areas:

  • Establishing a strong AI strategy;
  • Integrating AI-oriented operations;
  • Fostering a data-driven culture; and
  • Building ecosystems that increase and protect competitive differentiation.

Regardless of an organization’s commitment to AI adoption or its degree of success in implementing and scaling AI for strong outcomes, each area should be explored closely.


Organizations with an enterprise-wide AI strategy and leaders who communicate a bold vision were nearly twice as likely to achieve high outcomes among those surveyed than those without them.

One common key to success is maintaining a clear connection between AI efforts and the core business strategy, the survey data showed. Data scientists and information technology (IT) leaders should help senior executives determine which use cases offer the strongest opportunities for AI to help fulfill and expand the company mission.

Implementing AI should start with a clear, coordinated, real-time strategy across the enterprise that uses AI to gain a competitive edge and communicating that strategy to the workforce, partners, and customers.


Introducing AI technology and integrating it effectively requires reimagining and updating operational and governance processes. Leading organizations from the survey were more than three times as likely to have created new roles and changed operations, and were also three times as likely to document and enforce machine-learning operations (MLOps) procedures. However, two-thirds of surveyed organizations using AI have not yet adopted such operational AI leading practices as adhering to a well-calibrated MLOps framework, documenting AI life-cycle publication strategies, and updating workflows and roles across their organization.

Without these shifts, AI may not be adequately enabled to deliver on its potential. Organizations should embed AI into all core business processes and operations, and the C-suite should ensure it is weaving AI into the business decision-making fabric of the organization.

Making changes requires a thoughtful redesign of how work gets done and how the organization prepares itself to take advantage of new business models and opportunities as AI capabilities mature.

Culture and Change Management

Organizations that invest in change management are 1.5 times more likely to meet their goals than those that do not, according to Deloitte’s State of AI in the Enterprise report.

AI can supercharge the capabilities of a human workforce, freeing people from automated processes so they can focus on ideas that add value. However, organizations should support their workforce in upgrading skills and capabilities through tailored change management activities that address needs at all levels and functions.

Communicating AI’s benefits goes beyond touting it to the workforce. Changing minds generally takes education, motivation, and support. Establishing an acceptance of AI through change management often requires making the goals of AI transformation clear, relevant, and achievable to everyone in the organization.

For organizations that succeed in finding value in AI, one key difference among those surveyed has been in fostering a supportive AI-ready culture throughout the enterprise—engendering trust from employees that AI will benefit their work, building data literacy at all levels across the enterprise, and adopting agile processes that permit more (and more rapid) experimentation.


The organizations that achieve the best results from adopting AI into their strategies, operations, and cultures aren’t making this progress in a vacuum. They tend to build broad and diverse partnerships to support transformative visions for AI and strategies that span their enterprises to make AI a true value-adding differentiator.

And while this approach may feel counterintuitive, building diverse and complex ecosystems can be a safer strategy for an ecosystem-building organization than limiting partnerships to a small, streamlined network that entails fewer relationships to manage. Organizations that build complex networks with the right partners to help strategize and optimize their use of hardware, software, and AI applications may more easily adjust plans as necessary to achieve their goals into the future.

AI’s Role in Transformation

Evolving economic conditions increasingly illustrate AI’s potential to transform an organization in such ways as freeing the workforce to apply its innovation to create value, increasing operational speed and efficiency, meeting customer expectations at scale—and gaining an advantage over competitors that are slower to embrace AI’s capabilities. At every stage of its AI transformation journey, an AI-fueled organization should build AI strategy, operations, culture, and ecosystems to get the most out of its capabilities for their workforce and their customers.

Read Deloitte’s latest State of AI in the Enterprise report “Becoming an AI-Fueled Organization.”

About Deloitte: Please see for a detailed description of our legal structure.

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