4 Ways to Help Your Company Use AI More Effectively

4 Ways to Help Your Company Use AI More Effectively

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  • The overwhelming majority of leaders today consider their success dependent on strategies using artificial intelligence (AI) as tools to help them find and apply insights that improve decisions and outcomes.

    Of the 2,620 global business leaders the Deloitte AI Institute surveyed in 2022, 94% said they consider AI critical to their organizations’ success over the next five years. And 79% reported full-scale deployment for three or more types of AI applications: a dramatic increase over 62% in 2021.

    But many organizations are finding their outcomes falling short of their ambitions. Developing and deploying AI technology and practices isn’t enough on its own to unlock its fuller potential.

    Deloitte AI Institute’s State of AI in the Enterprise 5th Edition report classifies only 27% of surveyed organizations as AI “transformers” that have achieved strong results from AI transformation. Nearly as many organizations, 22%, are AI “underachievers” focused on developing AI without having used it effectively.

    Top challenges in getting started include proving AI’s business value, a lack of executive commitment, and the need to choose the right tools. Additional challenges to scaling AI projects include insufficient funding or technical skills to use it.

    Fortunately, underachievers can become transformers and tap AI’s hidden opportunities by taking four concrete actions:

    • investing in culture and leadership, to support new ways of working;
    • transforming operations, to support ethical AI at scale;
    • orchestrating tech and talent, to unleash greater human capabilities; and
    • selecting use cases that accelerate value in various operations and sectors.

    Supporting New Ways of Working

    A culture that supports AI is critical to transformation. Two out of five survey respondents say agility, embracing change, and an executive vision for using AI are the primary factors in creating an AI-forward culture.

    Those leaders who foster cross-organizational collaboration, actively nurture and retain AI professionals, and tap the workforce’s growing optimism for AI’s opportunities may see stronger results for their efforts.

    While much of the labor force once viewed AI with suspicion, 82% of survey respondents say the workforce now believes AI can help boost their performance and satisfaction as a collaborative tool to help humans make better decisions.

    To build trust in AI’s abilities to strengthen employees’ power, leaders should involve business specialists and frontline employees to design their AI, as the global retailer H&M did by involving merchandizers in testing and developing a sale-pricing algorithm—boosting both business results and employee goodwill toward AI.

    Implementing Ethical AI at Scale

    Getting the fullest rewards of AI requires redesigning operations to accommodate it and using it ethically by establishing clear processes and redefining roles around AI.

    Only one-third of the most recent survey’s respondents say their organizations have adopted best practices for redesigning their workflows for AI. For organizations trying to get up to speed on AI, ethics presents a real stumbling block: half of the survey respondents consider managing AI-related risks a top inhibitor to scaling AI projects.

    To embrace a transformational AI strategy, organizations need to take such steps as following documented machine-learning operations (MLOps) procedures, using documented processes for governance and quality of data, using common and consistent platforms for AI model and application development, and using risk-management processes to assess AI for bias and other risks.

    One financial services company, confronting such challenges as poor customer service and regulatory and compliance violations, paired its AI governance and risk-management specialists with its data scientists to build an ethical AI framework for managing its adoption responsibly, with better governance and controls, and greater workforce awareness and accountability for AI’s abilities and limits.

    Unleashing Greater Human Capabilities

    Organizations need to strategize by pairing AI and human capabilities—and skilled AI talent has long been in short supply.

    With AI improving and proliferating, 65% of survey respondents said their organizations adopt AI as off-the-shelf products or services, while 35% attempt to build customized systems and processes. Either approach can succeed; either way, transformational organizations are hiring outside AI expertise to help train internal resources, build custom tools, and find the right partners to collaborate in a fluid business environment.

    Acquiring that human capital today is a key challenge. “The most successful organizations I see are the ones that are investing in outside technical leadership,” a general manager of AI strategy at a nonprofit academic medical center said in the survey. “By investing in outside technical leadership, you’re bringing people onboard whose domain expertise is to answer these tough technical questions and give realistic feedback to nontechnical leaders.”

    Accelerating Value in Various Operations and Sectors

    Organizations setting out to implement their AI ambitions need to learn from the use cases that best support growth strategies for themselves and their sectors.

    Finding use cases that are relatively easy to achieve and yield clear results can build an internal momentum and cultural embrace that accelerate AI’s potential as a catalyst. Use cases that appear too complicated, too hard to communicate, or too limited in their returns may dampen the enthusiasm critical to an organization’s AI success.

    The processes and practices organizations need will guide AI strategies and decision making. Those needs vary by sector, and even within sectors: the prospect of cloud-pricing optimization may attract media and telecommunications, life sciences and health care, and energy, resources, and industrials; predictive maintenance may appeal more to government and public services; and voice assistants and chatbots may have applications for financial services to improve customer service.

    Deloitte AI Institute’s State of AI in the Enterprise 5th Edition report includes detailed use cases for how organizations apply AI to grow. With each, strategy drives adoption and implementation, not the other way around. And as more leaders determine how it can help more workforces help more customers, AI continues to increase its potential to help humans make better decisions at a speed and scale built for growth.


    Read Deloitte AI Institute’s latest State of AI in the Enterprise Report.

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