How to get Business Insights from Artificial Intelligence

The potential of Artificial Intelligence (AI) has filtered all the way up to top management in businesses around the world. Artificial Intelligence has many upsides for organizations, such as lower costs, better service quality, and the promise of fast, actionable business insights. The question is how can decision-makers lead their organizations towards harnessing the true power of AI-powered technology.

The market for AI technologies is booming, fueled in part by rising adoption by the enterprise. Results from a study byNarrative Sciencefound that 38% of enterprises are already using AI, and that number is set to grow to 62% by 2018. In thisForbes articlefrom earlier this year, Gil Press found that this is but one of many encouraging surveys:

AI is a complex field, and so, executives cannot just think of it as a process of applying isolated technical knowledge to a specific problem. Real value comes from understanding the vast array of technologies that underpin Artificial Intelligence, and how they can be used to develop full-service products.

Accenture’s comprehensive report on the potential of AI technologies for businesses,Turning Artificial Intelligence into Business Value. Today, sheds light on how to better understand the AI-aided solutions to your business goals. The report separates them in terms ofautomatingandaugmenting.For either category, companies need to asses solutions based on two criteria: work complexity, and data complexity.

Work complexity can span from routine, rule-based work (i.e. the work of a clerk officer), to ad-hoc tasks that require human judgement (i.e. the work of a research scientist). Similarly, data complexity can range from low-volume, structured data sets, such as sales reports, to high-volume, volatile data coming from social media, for example.

Analyzing the above mentioned criteria results in a framework, from which four primary types of activity models arise:

This model aims to provide consistent, cost-effective performance solutions with technology that senses and acts. Humans monitor accuracy and adjust rules based on business conditions. The systems translate these decisions into action quickly, accurately and efficiently.

This model includes so-called “expert systems”. These are able to survey massive data sets to make recommendations based on that knowledge.