In a time when data infrastructure and processing power offer the necessary foundations to fuel truly transformational applications and rapid innovation, artificial intelligence (AI) has a unique and powerful role to play in meeting many of the current challenges. 

The fifth edition of Deloitte’s annual State of AI in the Enterprise research explored how businesses are forging a path to a new future, one filled with unrealized sources of value. The report surveyed 2,620 executives from 13 countries, outlining detailed recommendations for leaders to cultivate an AI-ready enterprise and improve outcomes for their AI efforts.

• 94% of business leaders surveyed agree that AI is critical to success over the next five years.

• 79% of leaders say they have fully deployed three or more AI applications, compared to 62% last year.

• There was a 29% increase in the number of respondents self-identifying as “underachievers,” suggesting that many organizations are struggling to achieve meaningful AI outcomes.

• Top challenges associated with scaling according to respondents are managing AI-related risk (50%), lack of executive commitment (50%), lack of maintenance and post launch support (50%).

“Amid unprecedented disruption in the global economy and society at large, it is clear today’s AI race is no longer about just adopting AI — but instead driving outcomes and unleashing the power of AI to transform business from the inside out. This year’s report provides a clear roadmap for business leaders looking to apply next-level human cognition and drive value at scale across their enterprise.”, said Costi Perricos, Deloitte Global AI consulting partner.

The following key actions that many business leaders are taking to harness AI’s potential and drive value at scale across their enterprises emerged:

Action 1: Invest in Leadership and Culture

When it comes to successful AI deployment and adoption, leadership and culture matter. The workforce is increasingly optimistic, and leaders should do more to harness that optimism for culture change, establishing new ways of working to drive greater business results with AI.

• 82% of respondents indicate employees believe that working with AI technologies will enhance their performance and job satisfaction.

• The highest performing respondents were the most likely to report AI-ready cultural characteristics, such as: high cross-organizational collaboration; workforce optimism for the possibilities of AI; and actively nurturing and retaining AI professionals.

Action 2: Transform Operations

An organization’s ability to build and deploy AI ethically and at scale depends on how well they have redesigned their operations to accommodate the unique demands of new technologies.

• In both the fourth and fifth editions of this survey, operational best practices were associated with high outcomes, but most organizations have yet to make significant improvement in this area.

• Managing AI risk can have a major impact on an organization’s AI efforts, with 50% of respondents citing management of AI-related risks as one of the top inhibitors to starting and scaling AI projects.

Action 3: Orchestrate Tech and Talent

Technology and talent acquisition are no longer separate. Organizations need to strategize their approach to AI based on the skillsets they have available, whether they derive from humans or pre-packaged solutions.

• Given that even the most advanced organizations are still early in their transformations, a majority of organizations still prioritize bringing new AI talent into the business from outside, rather than retraining existing workers (53% versus 34%).

• A significant majority of the survey respondents acquire AI as a product or service (65%) rather than attempting to build their own AI solutions in-house (35%), leaning particularly on off-the-shelf solutions at the beginning of their journeys.

Action 4: Select Use Cases that Accelerate Outcomes

The report found that selecting the right use cases to fuel an organization’s AI journey depends largely on the value-drivers for the business based on sector and industry. Starting with use cases that are easier to achieve or have a faster or higher return on investment can create momentum for further investment and make it easier to drive internal cultural and organizational changes that accelerate the benefits of AI.

• The survey found the top use cases of AI across industries include cloud pricing optimization (44%); voice assistants, chatbots and conversational AI (41%); predictive maintenance (41%); and uptime/reliability optimization (41%).

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Source: State of AI in the Enterprise 2022