The 14 AI technologies businesses should be pursuing

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Extra about synthetic intelligence

Tech choice makers are more and more on the lookout for efficient methods to implement synthetic intelligence (AI) into enterprise and drive worth; nonetheless, not all AI applied sciences are value investing in, in response to Forrester’s latest Tech Tide report. Whereas all might not be value investing in, many are value experimenting with or sustaining use of, stated the report.

To assist enterprise leaders decide the AI know-how that’s value their time, the report targeted on 14 tech classes that help enterprise intelligence. Whereas the report discovered all 14 classes to be value pursuing, it separated the 14 into areas value both investing in, sustaining, or experimenting with.

SEE: Synthetic intelligence: Developments, obstacles, and potential wins (Tech Professional Analysis)

Every of the applied sciences accommodates or creates AI in some capability, helps firms uncover important enterprise insights, is commercially accessible at an enterprise scale, and has market potential or traction, stated the report.

The 14 classes have been separated into 4 quadrants: Experiment, make investments, keep, or divest. These value experimenting with had low maturity and low enterprise worth, which means enterprises ought to restrict their interplay with these applied sciences, stated the report. The applied sciences value investing in had low maturity and excessive enterprise worth. The keep part was for tech with excessive maturity and excessive enterprise worth, and the divest part was meant for tech with excessive maturity and low enterprise worth, stated the report.

The tech classes firms ought to spend money on included AI-enhanced enterprise intelligence platforms, automation-focused machine studying, deep studying frameworks, pure language understanding, and repair supplier AI platforms, in response to the report.

These value experimenting with included commercialized machine studying algorithms, laptop imaginative and prescient, machine olfaction, pure language era (NLG), and speech analytics, stated the report. And the tech value sustaining have been cognitive search, machine studying information catalogs, machine studying platforms, and textual content analytics, added the report.

Not one of the 14 classes ended up within the divest part, which suggests all of those classes nonetheless maintain high quality enterprise worth. And with AI persevering with to evolve and develop, not one of the tech was thought-about “outdated” but, in response to the report.

Take a look at this TechRepublic article to be taught extra about how AI drives worth in enterprise.

The large takeaways for tech leaders:

  • Forrester analyzed 14 AI know-how classes enterprise ought to both spend money on, keep, or experiment with. — Forrester, 2018.
  • No main AI applied sciences are value divesting in, as all nonetheless generate enterprise worth and are nonetheless evolving. — Forrester, 2018.

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