Four practices your organization might need to lead its AI transformation
Even though the pandemic has accelerated the transformation of many aspects of business, artificial intelligence (AI) has advanced over the past two years with notable speed.
As more leaders recognize and rely on the utility of AI to uncover and scale data-driven insights and free their people to creatively solve problems, they are seeing more in addition AI technologies and processes create value for employees, partners and customers.
Although we are only in the early days of AI transformation, organizations are rapidly developing and expanding their capabilities. A survey of 2,875 executives for Deloitte’s latest report State of AI in the enterprise report found that market-leading AI-focused organizations primarily focus on best practices in four key areas:
- Establish a strong AI strategy;
- AI-driven integration operations;
- Foster a data-driven approach 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 results, every area should be explored from close.
Organizations with an enterprise-wide AI strategy and leaders who communicate a bold vision were nearly twice as likely to score high among respondents than those without not.
One of the common keys to success is maintaining a clear link between AI efforts and core business strategy, survey data showed. Data scientists and information technology (IT) leaders need to help senior executives determine which use cases offer the best opportunities for AI to help fulfill and grow the business mission.
Implementing AI should start with a clear, coordinated, and real-time strategy across the enterprise that uses AI to gain competitive advantage and communicate that strategy to the workforce, partners, and to customers.
The introduction of AI technology and its effective integration requires rethinking and updating operational and governance processes. Top organizations in the survey were more than three times more likely to have created new roles and changed their operations, and were also three times more likely to document and apply machine learning operations procedures ( MLOps). However, two-thirds of organizations surveyed using AI have yet to adopt leading operational AI practices such as adherence to a well-calibrated MLOps framework, documentation of lifecycle release strategies AI and updating workflows and roles in their organization.
Without these changes, AI may not be able to fulfill its potential sufficiently. Organizations must embed AI into all core business processes and operations, and the C suite must ensure that it embeds AI into the fabric of business decision-making.
Bringing about change requires a thoughtful redesign of how work is done and how the organization prepares to take advantage of new business models and opportunities as AI capabilities mature.
Culture and change management
According to Deloitte, organizations that invest in change management are 1.5 times more likely to achieve their goals than those that don’t. Report on the state of AI in the company.
AI can boost the capabilities of a human workforce, freeing people from automated processes so they can focus on ideas that add value. However, organizations need to help their workforce improve their skills and capabilities through tailored change management activities that meet needs at all levels and functions.
Communicating the benefits of AI goes beyond bragging about it to the workforce. Changing mindsets usually requires education, motivation and support. Establishing AI acceptance through change management often requires making AI transformation goals clear, relevant, and achievable for everyone in the organization.
For organizations that are successful in finding value in AI, a key difference among respondents was fostering a supportive AI-ready culture across the enterprise, instilling employee trust that the AI will benefit their work, building data literacy at all levels of the business. , and adopting agile processes that allow for more (and faster) experimentation.
The organizations that achieve the best results by embracing AI in their strategies, operations, and cultures are not making this progress in a vacuum. They tend to build broad and diverse partnerships to support transformative AI visions and strategies that span their businesses to make AI a true value-added differentiator.
And while this approach may seem counter-intuitive, building diverse and complex ecosystems may be a safer strategy for an ecosystem-building organization than limiting partnerships to a small, streamlined network that involves fewer relationships to manage. . Organizations that create complex networks with the right partners to help them strategize and optimize their use of hardware, software, and AI applications can more easily adjust their plans as needed to achieve their goals in the future. .
The role of AI in transformation
Changing economic conditions increasingly illustrate the potential of AI to transform an organization by freeing up 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 who are slower to adopt AI. capacities. At every stage of its AI transformation journey, an AI-powered organization must build an AI strategy, operations, culture, and ecosystems to make the most of its capabilities for its employees and customers. .
Read Deloitte’s latest report on the state of AI in the enterprise »Become an AI-powered organization.”
About Deloitte: please look www.deloitte.com/us/about for a detailed description of our legal structure.