At A Glance: AI can change the way the world’s businesses operate, yet organizations are failing to utilize this powerful tool to its full potential. Here are 3 shifts organizations should implement to fully capitalize on AI capabilities.
Market Segment: General; Business
Artificial Intelligence is the future of business -- there’s no doubt about it. Yet, for all the efficiency and data insights AI and Machine Learning brings, progress has been slow, largely due to formidable cultural and organizational barriers that make it difficult to rewire organizations to be optimized for AI. According to surveys with thousands of executives conducted by Harvard Business Review, only 8% of firms engage in core practices that support widespread adoption.
Excitement about AI opportunities often cause leaders to make mistakes with implementation, such as expecting immediate returns on investments and thinking too narrowly about AI requirements for success. Below are three shifts companies must make in order to transform small AI pilots into company-wide AI successes.
From silos to interdisciplinary collaboration
Instead of implementing AI on a set of isolated business issues, having business, analytics, and operational experts working together with AI tools will ensure that solutions address broad organizational priorities. Having diverse teams working on new applications dramatically increases the chances of widespread adoption and encourages creative solutions to any implementation issues.
Transition from experience-based decision making to data-driven decision-making
In order for companies to take advantage of AI’s insights, employees at all levels must trust the algorithm’s suggestions and feel empowered to make decisions based on these insights without consulting higher-ups. Without abandoning the traditional top-down approach to decision-making, companies will not be able to fully take advantage of the benefits of AI.
From risk-averse to agile, experimental thinking
In AI adoption, employees and organizations should shed the belief that an idea needs to be fully developed or possess every desired functionality before deployment. As AI applications rarely have all their desired functionality upon initial adoption, a test-and-learn mentality instead frames mistakes as discoveries from which improvements can be made, allowing firms to correct small issues and prevent large costly problems.
Such shifts will not come easy, and leaders must work to prepare, motivate, and equip not just their workforce, but also themselves to capture the full benefits of AI implementation.
To learn more, read the original article on Harvard Business Review; Building the AI-Powered Organization
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