Artificial Intelligence Myths and Realities

While business leaders are paying attention to change brought about by AI technology, many make costly mistakes or fail to move forward due to factors that include bad advice and myths of AI. The table below dispels common myths about AI.

1Technology companies will be the primary beneficiaries of AIMany non-tech companies have created or expect to generate value from AI
2The availability of sophisticated AI tools will level the playing fieldThe gap between leaders and laggards is widening, with the leaders doubling down on AI investment
3The primary benefit of AI is cost savings from automationMost companies use AI to increase revenues and improve quality in addition to reducing costs
4Senior leaders expect AI to reduce the size of their workforceThe more the senior the executive, the less likely they are to believe that AI will lead to overall job loses
5Organizations can scale AI successfully by increasing the number of pilot projectsScattered pilot projects do not fully unlock the value hidden in data and organizational knowledge; they add risk to the organization
6AI is available as software packages and plug n’ play solutionsAn AI solution is built for a specific problem, using specific data and specific domain knowledge; no two AI solutions are identical
7Organizations need PhDs, data scientists, coders, machine learning experts, and huge budgets to use AI successfullyThere are several enterprise-grade AI software tools that are accessible to the common user and requiring modest budgets and their number is increasing
8Giant internet companies have a monopoly over data that can be used to make AI applicationsData is verticalized; companies can have more data in their domain than the giant internet companies, enabling them to create something unique
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