AI innovation is occurring at a fast clip, with a number of technologies on the “hype cycle” reaching mainstream adoption within two to five years. That’s according to Gartner, which today released a report identifying four trends driving near-term AI innovation in the enterprise. It finds that while the AI industry remains in an “evolutionary state,” technologies including edge AI, computer vision, decision intelligence, and machine learning are poised to have a transformational impact on markets in coming years.
Gartner sees evidence of a trend of companies seeking capabilities beyond what current AI tools can often accomplish. Organizations are focusing on implementation, risk management, and ethics as they look to scale AI initiatives. But data leaders run the risk of failing to realize value from these initiatives if they don’t “prioritize and accelerate” investments in AI technologies at various stages of maturity, Gartner warns.
Responsible AI
Increased trust, transparency, fairness, and auditability of AI technologies continues to be of growing importance to a range of stakeholders, according to Gartner. “Responsible AI” can help to achieve a semblance of fairness, trust, and regulatory compliance — even if biases are baked into the data and explainability methods fall short. For this reason, Gartner expects that all experts hired for AI development and training work will have to demonstrate competence in responsible AI by 2023.
Continue reading: https://venturebeat.com/2021/09/07/ai-focus-shifts-to-small-and-wide-data/
Gartner sees evidence of a trend of companies seeking capabilities beyond what current AI tools can often accomplish. Organizations are focusing on implementation, risk management, and ethics as they look to scale AI initiatives. But data leaders run the risk of failing to realize value from these initiatives if they don’t “prioritize and accelerate” investments in AI technologies at various stages of maturity, Gartner warns.
Responsible AI
Increased trust, transparency, fairness, and auditability of AI technologies continues to be of growing importance to a range of stakeholders, according to Gartner. “Responsible AI” can help to achieve a semblance of fairness, trust, and regulatory compliance — even if biases are baked into the data and explainability methods fall short. For this reason, Gartner expects that all experts hired for AI development and training work will have to demonstrate competence in responsible AI by 2023.
Continue reading: https://venturebeat.com/2021/09/07/ai-focus-shifts-to-small-and-wide-data/
