Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. At AWS re:Invent this week, Amazon launched AWS AI Service Cards, a form of responsible AI documentation meant to help customers better understand the AI services offered by the cloud computing leader. According to Gartner analyst Svetlana Sicular, the AWS AI Service Cards are a signal that Amazon is making moves to catch up with its competitors when it comes to embracing responsible AI. In the past, Amazon "denied responsible AI" and fell behind its competitors, including Microsoft and Google, in addressing responsible AI issues, Sicular told VentureBeat. But Amazon has "a very good history of catching up when they put their mind and the effort and resources to catching up," she said.

Microsoft says it wants to make it easier for organizations to use and build AI technology responsibly. During its "Put Responsible AI into Practice" digital event on Dec.7, the tech giant, with Boston Consulting Group, released 10 guidelines that product leaders can use to implement AI responsibly, without bias and with visibility into the intentions of AI and machine learning algorithms. Enterprises can use the guidelines before, during, and after of the process of building AI models. Microsoft outlines the guidelines in a three-step framework that starts with using transparent processes to assess and prepare the model and weigh potential risks and benefits. The next step is design, build, and document.

Four trends on the Gartner, Inc. Hype Cycle for Artificial Intelligence, 2021 are driving near-term artificial intelligence (AI) innovation. These trends include responsible AI; small and wide data approaches; operationalization of AI platforms; and efficient use of data, model and compute resources. "AI innovation is happening at a rapid pace, with an above-average number of technologies on the Hype Cycle reaching mainstream adoption within two to five years," said Shubhangi Vashisth, senior principal research analyst at Gartner. "Innovations including edge AI, computer vision, decision intelligence and machine learning are all poised to have a transformational impact on the market in coming years." The AI market remains in an evolutionary state, with a high percentage of AI innovations appearing on the upward-sloping Innovation Trigger .

Four trends on the Gartner, Inc. Hype Cycle for Artificial Intelligence, 2021 are driving near-term artificial intelligence (AI) innovation. These trends include responsible AI; small and wide data approaches; operationalization of AI platforms; and efficient use of data, model and compute resources. "AI innovation is happening at a rapid pace, with an above-average number of technologies on the Hype Cycle reaching mainstream adoption within two to five years," said Shubhangi Vashisth, senior principal research analyst at Gartner. "Innovations including edge AI, computer vision, decision intelligence and machine learning are all poised to have a transformational impact on the market in coming years." The AI market remains in an evolutionary state, with a high percentage of AI innovations appearing on the upward-sloping Innovation Trigger (see Figure 1).

Research firm Gartner has identified four trends that are driving artificial intelligence innovation in the near term. Stakeholders are demanding increased trust, transparency, fairness and auditability of AI technologies, according to Svetlana Sicular, research vice president at Gartner. Responsible AI provides a governance framework for meeting those requirements: "Responsible AI helps achieve fairness, even though biases are baked into the data; gain trust, although transparency and explainability methods are evolving; and ensure regulatory compliance, while grappling with AI's probabilistic nature," Sicular said. Gartner contends that AI models based on large amounts of historical data have become less relevant as organizations have undergone sweeping changes during the COVID-19 pandemic. Today, small data -- which Gartner defines as "the application of analytical techniques that require less data but still offer useful insights" -- and wide data -- "data that enables the analysis and synergy of a variety of small and large, unstructured and structured data sources" -- enable more robust analytics for decision-making.

According to the latest AI hype cycle from Gartner, the AI market remains in an evolutionary state, with a high percentage of innovations appearing on the upward-sloping early stage, named the'Innovation Trigger'. This finding indicates a market trend of end users seeking specific technology capabilities that are often beyond the capabilities of current AI tools. Meanwhile, smart robots, knowledge graphs, edge AI and digital ethics are among the trends at the'Peak of Inflated Expectations'. "AI innovation is happening at a rapid pace, with an above-average number of technologies on the Hype Cycle reaching mainstream adoption within two to five years," said Shubhangi Vashisth, senior principal research analyst at Gartner. "Innovations including edge AI, computer vision, decision intelligence and machine learning are all poised to have a transformational impact on the market in coming years."

AMAZON'S "GO" STORES are impressive places. The cashier-less shops, which first opened in Seattle in 2018, allow app-wielding customers to pick up items and simply walk out with them. The system uses many sensors, but the bulk of the magic is performed by cameras connected to an AI system that tracks items as they are taken from shelves. Once the shoppers leave with their goods, the bill is calculated and they are automatically charged. Doing that in a crowded shop is not easy.

In 2021, artificial intelligence (AI) augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally, according to Gartner. Gartner defines augmented intelligence as a human-centered partnership model of people and AI working together to enhance cognitive performance. This includes learning, decision making and new experiences. "Augmented intelligence is all about people taking advantage of AI," said Svetlana Sicular, research vice president at Gartner. "As AI technology evolves, the combined human and AI capabilities that augmented intelligence allows will deliver the greatest benefits to enterprises."

When SAP veteran Bill McDermott took over the CEO spot at digital workflow company ServiceNow in October, his mandate focused on growth. "Should we choose to do'tuck-ins' to compliment what our customers need, to get us somewhere faster, we'll do that very carefully," he told CNBC. ServiceNow kicked off 2020 with one such "tuck-in": the acquisition of Israeli company Loom Systems, an AIOps company that uses artificial intelligence to give enterprise users insights into digital operations and fix IT issues. The acquisition symbolizes a bigger trend in enterprise technology: Acquiring AI startups enables technology vendors to capitalize, enhance or expand their capabilities while bringing scarce talent aboard. Last year, consolidation in the AI market hit record numbers.

Artificial intelligence uses vast amounts of data and sophisticated probabilistic algorithms to offer "the intimacy of a small town in a big city scale," Gartner VP Svetlana Sicular said at the company's annual IT Symposium last week. But she said, the growth of AI applications in deployment was actually less this year than last year, with the total percentage of CIOs saying their company has deployed AI now at 19 percent, up from 14 percent last year. That's a nice increase, but it's far lower than the 23 percent of companies that thought they would newly roll out AI in 2019. She said, "something is stalling AI adoption." She noted that when asked what challenges they faced in adopting AI, the top concerns are the lack of skills on staff, the quality of the data they have available, and also understanding the real benefits and uses of AI.