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Senén Barro and Thomas H. Davenport
Thoughtful adoption of intelligent technologies will be essential to survival for many companies. But simply implementing the newest technologies and automation tools won’t be enough. Success, the authors argue, will depend on whether organizations use them to innovate in their operations and in their products and services — and whether they acquire and train the human capital to do so.
Surveys show that most senior executives believe AI will substantially transform their organizations within the next few years, which means humans will need to find ways to work closely with machines. Few organizations have begun the necessary job redesign, re-skilling, or retraining programs, the authors say. Moreover, most individuals aren’t being adequately prepared for automation-enabled work. Smart organizations will need to adopt intelligent technologies, and they will need to recruit and retrain people for skilled roles and redesign tasks and jobs. What’s more, they will need to use artificial intelligence as an enabler of innovation in products, processes, and business models. Rather than being implemented systematically, the authors expect “innovation based on intelligent automation” to occur on a job-by-job, task-by-task basis.
While the potential for AI-enabled innovation exists in virtually every aspect of business and society, the authors say it is largely unrealized today. Technology vendors are conceiving and producing innovations ranging from self-driving cars and trucks to the “self-driving enterprise.” But few would-be adopters have even begun the process of envisioning how AI will change jobs in their companies and what new skills must be developed.
David Kiron and Michael Schrage
Executives intent on exploiting AI to enhance processes or products tend to focus on having a strategy for AI. But creating strategy with AI can matter as much or even more.
What does strategy with AI mean? Like any corporate strategy, it expresses what enterprise leaders deliberately seek to emphasize over a given time frame. It articulates how and why the organization expects to succeed in its chosen market. These aspirations might involve, for example, superior customer experience and satisfaction, increased growth or profitability, greater market share, or agile fast-followership.
Whatever the specific strategy, virtually all organizations create corresponding measures to characterize and communicate desirable strategic outcomes. In a machine learning era, enterprise strategy is defined by the key performance indicators (KPIs) leaders choose to optimize.