Artificial Intelligence

The 14 AI technologies businesses should be pursuing

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Tech decision makers are increasingly looking for effective ways to implement artificial intelligence (AI) into business and drive value; however, not all AI technologies are worth investing in, according to Forrester’s recent Tech Tide report. While all may not be worth investing in, many are worth experimenting with or maintaining use of, said the report.

To help business leaders determine the AI technology that is worth their time, the report focused on 14 tech categories that support business intelligence. While the report found all 14 categories to be worth pursuing, it separated the 14 into areas worth either investing in, maintaining, or experimenting with.

SEE: Artificial intelligence: Trends, obstacles, and potential wins (Tech Pro Research)

Each of the technologies contains or creates AI in some capacity, helps companies uncover vital business insights, is commercially available at an enterprise scale, and has market potential or traction, said the report.

The 14 categories were separated into four quadrants: Experiment, invest, maintain, or divest. Those worth experimenting with had low maturity and low business value, meaning enterprises should limit their interaction with those technologies, said the report. The technologies worth investing in had low maturity and high business value. The maintain section was for tech with high maturity and high business value, and the divest section was intended for tech with high maturity and low business value, said the report.

The tech categories companies should invest in included AI-enhanced business intelligence platforms, automation-focused machine learning, deep learning frameworks, natural language understanding, and service provider AI platforms, according to the report.

Those worth experimenting with included commercialized machine learning algorithms, computer vision, machine olfaction, natural language generation (NLG), and speech analytics, said the report. And the tech worth maintaining were cognitive search, machine learning data catalogs, machine learning platforms, and text analytics, added the report.

None of the 14 categories ended up in the divest section, which means all of these categories still hold quality business value. And with AI continuing to evolve and develop, none of the tech was considered “outdated” yet, according to the report.

Check out this TechRepublic article to learn more about how AI drives value in business.

The big takeaways for tech leaders:

  • Forrester analyzed 14 AI technology categories business should either invest in, maintain, or experiment with. — Forrester, 2018.
  • No major AI technologies are worth divesting in, as all still generate business value and are still evolving. — Forrester, 2018.

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