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Enterprises will gamify strategic planning, build simulations in the boardroom, and move into intelligent edge experiences, said the report. Unsplash

In 2021, one in four forward-thinking enterprises will push Artificial Intelligence to new frontiers, such as holographic meetings for remote work and on-demand personalised manufacturing, according to new predictions by Forrester Research.

They will gamify strategic planning, build simulations in the boardroom, and move into intelligent edge experiences, said the report.


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Consultancies like Capgemini, EY, and KPMG will provide strategy and governance chops, while software companies like DataRobot, IBM, and Tecton will provide scale and speed to fuel this imagination, it added.

“Plan to quadruple your investment next year. Build your internal AI team, engage consultancies to implement domain-specific solutions, and upgrade your data, analytics, and machine learning (ML) platforms to rethink how you use AI,” Forrester advised.

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But here are many deterrents to AI success — a lack of trust, poor data quality, data paucity, a lack of imagination, and a dearth of the right power tools to scale.

However, the next year will see companies tackle these head on, not because they want to or suddenly have the wherewithal to overcome these in this unprecedented year, but because they have to.


While synthetic data allows users to create data sets for training AI, fake data does the opposite — it perturbs training data to deliberately throw off AI. Unsplash

“They have to rebuild their businesses not for today or even next year but to prepare to compete in an AI-driven future,” Forrester said.

With this expected hypergrowth in AI, there will also be the proliferation of artificial data and the beginnings of a blockchain-based approach to data trust.

Want to read more in Hindi? Checkout: नोरा फतेही ने डांसर के संघर्ष को लेकर की बात

Artificial data comes in two related but different forms: synthetic data and fake data.

While synthetic data allows users to create data sets for training AI (Artificial Intelligence), fake data does the opposite — it perturbs training data to deliberately throw off AI.

Artificial data have many pros and cons. The good part is that they can help data-strapped organisations to adopt AI by turning to synthetic data providers like DataGen and Mostly AI.

Also Read: How to Check if Something is an Online Scam

At the same time malicious actors can use fake data in adversarial attacks like the one that caused a Tesla last year to veer into oncoming traffic due to stickers placed on the road.

Blockchain for data provenance will begin to repair AI’s trust problem, according to Forrester. (IANS)


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