Analyst predictions for AI in 2023

Analyst predictions for AI in 2023

Me: “Alexa, tell me what will happen in 2023.”

Amazon AI: “Sorry, I can’t predict the future.”

As the abundance of forecasts for 2023 asserts, humans always win in the futures market. Or maybe they’re just not as modest as Alexa (or Amazonians feed it with answers to common questions).

Observations of the computing landscape and AI developments are certainly far from modest, using their clear crystal balls to conjure up many and varied predictions about what will happen in 2023. Here is a brief summary.

Automated software development

Forrester called the AI ​​that writes code “TuringBots” already two years ago, when it was only used for software testing. Now he predicts that in 2023 TuringBots will write 10% of the world’s code and tests. Due to the increasing automation of software development, IDC predicts that the job of a software developer will shift more into a management and orchestrating role and become very complex. This will have a specific impact on the development of AI programs – IDC predicts that by 2024, most organizations will leverage no-code development tools for at least 30% of their AI and automation initiatives , “helping to scale digital transformation and democratize AI.”

Automated content and commerce

With generative AI producing, in addition to software code, a variety of new content such as images, videos, music, speech and text, Gartner predicts that by 2025, 30% of outgoing messages large organizations will be generated synthetically. Forrester predicts that by 2023, 10% of Fortune 500 companies will generate content with AI tools, such as “hHuman-produced content creation will never be fast enough to meet the need for personalized content at scale. IDC predicts that by 2026, the massive base models (> trillions of parameters) behind this automated content development “will become industry-standard utilities provided only by the largest vendors”.

Beyond content development, Gartner says CEOs and CIOs believe a fifth of their total revenue could come from “machine customers” by 2030. It will be non-human economic actors who will get goods or services in exchange for payment. By 2026, Gartner predicts that half of B2B buyers will interact with a digital human in a buying cycle. “Digital humans will take on tasks that humans don’t want to do, such as managing lead nurturing, old opportunities, or leads that went nowhere.”

Corporate governance, risks, sustainability and security

By 2026, IDC predicts, 75% of large enterprises will rely on AI-powered processes to improve asset efficiency, streamline supply chains, and improve product quality in diverse and distributed environments .

With AI in every corner of the business, increasing regulation and growing demand for responsible AI will drive one in four CIOs and CTOs to lead AI governance for their business, Forrester predicts. AI governance will become a board-level topic along with cybersecurity and compliance. The board’s reports, according to Forrester, will include “explainability, fairness audits of high-impact algorithmic decision-making, and environmental impacts of AI.”

IDC predicts that in response to concerns of sustainability and economic uncertainty, 40% of G2000 members will adopt tools to quantify, predict, and optimize the cost-benefit of their AI lifecycle by 2024. Gartner warns that without sustainable AI practices, by 2025 AI will “consume more energy than human labor, significantly offsetting zero carbon gains. If current AI practices remain unchanged , Gartner estimates that the energy needed to train machine learning and store and process the associated data could account for up to 3.5% of global electricity consumption by 2030.

As AI models become mission-critical, model risk and governance will take more of a company’s focus, until by 2025, 60% of G2000 CFOs are integrating AI risk into their business. their enterprise risk management programs, predicts IDC.

Consumer interactions and experiences

According to Forrester, 65% of B2B marketers with conversation automation today use AI-powered virtual assistants to engage and activate customer and employee audiences. In 2023, companies will continue to experiment with AI personas as brand assets as companies seek to differentiate these conversational interactions by demonstrating respect and relevance to the customer.

Gartner estimates that there are approximately 17 million contact center agents worldwide today. According to Gartner, 10% of agent interactions will be automated by 2026, an increase from the estimated 1.6% of interactions today that are automated using AI. By 2026, conversational AI deployments in contact centers will reduce agent labor costs by $80 billion.

In 2023, Forrester predicts that AI systems will use insurance coverage, diagnosis, location, availability, and cancellation risk factors to optimize healthcare planning workflows. The data will be used to fill in the costly gaps of last-minute cancellations, as smart systems contact waitlisted patients based on their predicted likelihood of responding. Addressing this issue will reduce the average wait of 20.6 days to see a doctor by 25%, Forrester estimates: “Retail healthcare will be spearheading this initiative which will cause seismic disruption and increasing traditional healthcare organizations to improve their patient experience.

AI has become mainstream, with 73% of data and analytics decision makers developing AI technologies and 74% seeing a positive impact in their organizations, according to the 2022 Data and Analytics Survey. Forrester analysis.

AI has also advanced by leaps and bounds. My dialogue with Alexa reported above shows a huge improvement over a similar dialogue at the end of 2018, when to my question regarding what will happen next year, Alexa replied “Do you want to open” this day in the story “?”

This may indicate a considerable improvement in the deployment of AI (from Amazon, in this case), but over the last three years we’ve also seen a huge improvement in the development of AI, leading to new (and surprising, given what we’ve learned from the year-end forecast) capabilities.

Large language models, also known as base models, have led to a number of surprises in 2022. The most recent is ChatGPT, released on November 30, which took just five days to surpass one million users. Many of these users were software developers, seeking help from ChatGPT to solve their coding problems.

“Stack Overflow, the go-to Q&A site for coders and programmers, has temporarily banned users from sharing answers generated by the AI ​​chatbot ChatGPT,” reported The Verge. “ChatGPT simply allows users to generate answers too easily and flood the site with answers that seem correct at first glance, but are often wrong upon closer examination.”

A safe prediction for 2023 is that we will continue to be surprised by new AI hits and misses. A sure prediction for 2023 is what Oren Etzioni recently told the The Wall Street Journal: “Six months from now you’re going to see amazing things that you haven’t seen today.”


Forrester Predictions 2023: Artificial Intelligence

IDC FutureScape: 2023 predictions for artificial intelligence and automation around the world

Gartner Top 10 Strategic Technology Trends for 2023

#Analyst #predictions

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