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    Profit Potential Driving ‘All In’ Deployment Plans for AI

    By
    DENNIS MCCAFFERTY
    -
    December 12, 2018
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      1Profit Potential Driving ‘All In’ Deployment Plans for AI

      Profit Potential Driving 'All In' Deployment Plans for AI

      A notable share of companies intend go “all in” on artificial intelligence (AI) initiatives, planning to implement AI enterprisewide in 2019, according to a recent survey from PwC. In doing so, organizations expect to boost profits, create a better customer experience (CX) and improve decision-making. To ensure that their workforce is up to the challenge, most businesses plan to launch continuous learning sessions that focus on this emerging technology, while identifying new skills and roles to effectively leverage it. More than 1,000 U.S. executives at companies either implementing AI or seriously considering doing so took part in the research. The following slide show presents highlights from the survey, with charts provided courtesy of PwC.

      2Companies Commit to AI Deployments

      Companies Commit to AI Deployments

      PwC reports that 43 percent of organizations have either implemented artificial intelligence (AI) in multiple areas or are piloting it. One-fifth of companies plan to implement AI enterprisewide in 2019.

      3Dedicated Centers ‘Own’ AI Efforts

      Dedicated Centers 'Own' AI Efforts

      Nearly one-quarter of businesses have established an “AI center of excellence” to oversee these deployments. For 19 percent of companies, a data and analytics group oversees AI initiatives.

      4Continuous Learning Required for Prepared Workforce

      Continuous Learning Required for Prepared Workforce

      To build a workforce that’s prepared for these changes, 60 percent of companies are planning to launch continual learning initiatives that include AI, and 56 percent intend to develop a workforce plan that identifies new skills and roles needed as a result of AI. Nearly one-half anticipate changing performance and development frameworks to include AI skills.

      5Security Boosts Trust Factor

      Security Boosts Trust Factor

      “Responsible AI”—meaning that the technology is implemented in a trustworthy, fair and stable way—has emerged as an ongoing discussion within enterprises these days. To ensure this, 64 percent of companies plan to boost AI security with validation, monitoring and verification.

      6Transparency Distinguishes Integrity of Efforts

      Transparency Distinguishes Integrity of Efforts

      More than three of five organizations plan to support “responsible AI” by creating transparent, explainable and provable AI models. And 55 percent intend to create systems that are ethical, understandable and legal.

      7Integration Tops Priority List

      Integration Tops Priority List

      The integration of AI and analytics systems has emerged as the top AI data-related priority, as cited by 58 percent of survey respondents. Nearly one-half cited the need to ensure that data in AI systems meets regulatory requirements.

      8Data Identification/Aggregation Playing Key Role

      Data Identification/Aggregation Playing Key Role

      The need to identify and aggregate data throughout the organization is considered another top AI data-related priority, as cited by 47 percent of respondents. Thirty-six percent cited the need to integrate internet of things (IoT) data so it can be used by AI systems.

      9Companies Anticipate Increased Profits, Better CX

      Companies Anticipate Increased Profits, Better CX

      In terms of needed ROI, 48 percent of respondents said they expect their AI efforts to increase revenues and profits. Forty-six percent said they want to create a better customer experience (CX), while 40 percent are seeking to improve decision-making.

      10Proving ‘Trustworthy’ AI Emerges as Major Challenge

      Proving 'Trustworthy' AI Emerges as Major Challenge

      In listing the top AI challenges, 37 percent of respondents cited the need to ensure AI systems are trustworthy. Thirty-six percent cited the need to train employees to work with AI, and 36 percent cited the need to converge AI with other technologies.

      PrevNext

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