2022 AI Predictions: Talent Shortage to Drive Automation; Supply Chains to Update Tech
Automakers partnering with AI startups; microfactories coming; bots on front lines for hyper-convenience; language models to get larger; AI Compliance Officer needed; bias-detecting to be employed
By John P. Desmond, Editor, AI in Business (firstname.lastname@example.org)
[Ed. Note: We have heard from a range of AI practitioners with predictions for the impact of AI in 2021. Here is a selection:]
From Doug Gilbert, CIO and Chief Digital Officer, Sutherland, offering business process transformation services:
Businesses held captive by AI. Early adopters of rudimentary enterprise AI embedded in ERP/CRM platforms are starting to feel trapped. In 2022, we'll see organizations take steps to avoid AI lock-in. And for good reason. AI is extraordinarily complex. When embedded in, say, an ERP system, control, transparency and innovation is handed over to the vendor not the enterprise. AI shouldn't be treated as a product or feature: it's a set of capabilities. AI is also evolving rapidly, with new AI capabilities and continuously improved methods of training algorithms. To get the most powerful results from AI, more enterprises will move toward a model of combining different AI capabilities to solve unique problems or achieve an outcome. That means they'll be looking to spin up more advanced and customizable options and either deprioritizing AI features in their enterprise platforms or winding down those expensive but basic AI features altogether.
Dumb bots get smart with advanced natural language understanding. Today's chatbots have proven beneficial but have very limited capabilities. Natural language processing will start to be overtaken by neural voice software that provides near real time natural language understanding (NLU). With the ability to achieve comprehensive understanding of more complex sentence structures, even emotional states, break down conversations into meaningful content, quickly perform keyword detection and named entity recognition, NLU will dramatically improve the accuracy and the experience of conversational AI.
This will result in: conversational AI being capable of real-time human assistance, such as supporting an employee through language translation, or recommending responses based on behavior or based on skill level; and a change in perception by customers as to how they are being treated, with NLU delivering a more natural and positive experience.
Flexible work models spur demand for new security measures beyond traditional cybersecurity. When employees work from anywhere, IT has to deal with traditional cybersecurity threats, plus additional threats from employees' physical environments. For example, if an employee who deals with highly sensitive information is working from home or a coffee shop, they not only need to be concerned about a phishing attack, but also someone looking over their shoulder or taking a photo of private company data such as customer personally identifiable information (PII). With flexible work models becoming the norm, demand will grow for new approaches for addressing this growing risk.
From Max Reynolds, CEO and cofounder, Symbio Robotics, supporting industrial automation:
The pandemic and labor shortage will create a more augmented workforce. As a result of the pandemic and the Great Resignation, we are experiencing a shortage of technical and skilled labor and tribal knowledge, which is predicted to continue in 2022 and beyond. In fact, Gartner, reports the talent shortage is the biggest barrier to the adoption of 64 percent of new technologies. Available talent to help companies adopt IT automation technologies is of particular concern, with 75 percent of leaders reporting it as the main risk factor. In 2022, we will see a more augmented workforce making greater use of smart tools and automated services to help workers be more efficient. More of us will find such smart tools a part of our everyday working lives.
The global chip shortage will continue to exacerbate the need for flexible manufacturing.
We will continue to feel the impacts of the chip shortage in 2022, resulting in further delays or short supply of tech components and products. Good production planning and the ability to ramp up production capacity quickly to catch up to these delays will become increasingly important.
Competition between legacy automakers and the newbies will heat up. In 2022, we’ll continue to see a shift in the dynamics of automotive — tech companies aren’t just nipping at the heels of the big automakers, they are legitimate competitors. The marrying of technology and automotive due to EV demand has the competitive juices flowing as tech giants continue their foray into the automotive space. We see a lot of activity — Tesla is a trillion-dollar company, Lucid passes Ford in value, Rivian sees the biggest IPO this year, Foxconn acquired a chip plant as it looks to make auto chips amid its foray into the electric vehicle (EV) market. That said, I see the incumbents retaining competitive advantage. As startups continue to get millions and billions in funding, how do they catch up and keep up to deliver on expectations and valuation of their company?
It’s a different competitive advantage as large automotive companies partner with high-tech startups to retain their competitive edge. Large automakers have economies of scale. We need to pivot production to make it more flexible to build something different while maintaining economies of scale.
Supply chains will further impact supply, not demand. Major supply chain issues will continue to delay the production of goods and services in 2022. However, the demand will continue to increase. We’ll see companies investing in flexible manufacturing at a high rate to try to catch up. In the automotive industry, this means trying to crank out as many cars as possible to fill the lots and meet demand in the market. Supply chains should take the time to update and automate their technology to win the race in the long run.
Smaller, ultra-efficient, easily built micro-factories will help companies ‘build back better.’
We’ll see less conventional large-scale global manufacturing in 2022 as manufacturing companies look to not only recover from the challenges of the pandemic but build products more efficiently. Microfactories will challenge conventional assumptions about vehicle design and production. The resulting benefits will include higher operating efficiency, reduced supply chains, and lower environmental impact.
From Rick Bentley, CEO of Cloudastructure, offering a video surveillance platform:
AI is the Future of Video Surveillance. Not long ago, if you wanted a computer to recognize a car then it was up to you to explain to it what a car looks like: “It’s got these black round things called ‘wheels’ at the bottom, the ‘windows’ kind of go around the top half-ish part, they’re kind of rounded on top and shiny, the lights on the back are sometimes red, the ones up front are sometimes white, the ones on the side are sometimes yellow…”. As you can imagine, it doesn’t work very well. Today you just take 10,000 pictures of cars and 50,000 pictures of close-but-not cars (motorcycles, jet skis, airplanes…) and your AI/ML platform will do a better job of detecting cars than you ever could.
Intelligent AI- and ML-powered video solutions are the way of the future, and if businesses don't keep up, they could be putting themselves and their employees at risk. Two years ago, more than 90 percent of enterprises were still stuck on outdated on-premises security methods, many with limited or no AI intelligence. The industry is undergoing rapid transformation as they take advantage of this technology and move their systems to the cloud.
Enhanced AI functionality and cloud adoption in video surveillance have allowed business owners and IT departments to monitor the security of their businesses from the safety of their homes. The AI surveillance solution can be accessed from any authorized mobile device and the video is stored safely off premises so that it cannot be hacked, and it is safe from environmental hazards. Additionally, powerful AI analytics allow intelligent surveillance systems to sort through large volumes of footage to identify interesting activity more than 10x faster and more accurately than manual, on-premises solutions. In the upcoming years, AI functionality will continue to get more and more advanced, allowing businesses to generate real-time insight and enable a rapid response to incidents resulting in a more efficient and safer society.
From Rich Green, Chief Technology Officer, SugarCRM, offering a customer relationship management platform.
AI and Bots Will Address the Need for Speed in 2022. Now more than ever, time compression is everywhere. Popular online “speed-to-serve” masters such as Amazon and Uber have conditioned us that we should never have to wait. Today, speed is a critical customer experience issue.
Responding to a lead must be done in seconds or minutes; time to complete a Service Level Agreement must be highly accelerated; and responding to a customer support question must be sufficiently quick to prevent wait times that evolve into a poor review.
Organizational models and technologies need to evolve to keep up with increasing speed-to-serve expectations. Sales, marketing, and service need to operate as one team, with hand offs in seconds and back-and-forth responses in minutes. Data must be shared, and data-driven processes, priorities, next steps, and outlooks automated via AI.
In sales, marketing and service, bots will become the front line for “hyper convenient” engagement as a first step before getting routed to a human. Bots will handle tedious tasks and increasingly offload significant amounts of manual, repetitive work, freeing humans to focus on more inspired, value-added work, while meeting the need for speed in 2022.
2022 – The Year AI Breaks Through the “Human Trust” Barrier
Marketeers don’t yet trust AI – 2022 is the year that they will.
Companies are still cautious about relying on AI to analyze and automate business processes, so they work in a “dual mode” of people and AI until they feel confident in the AI skills. 2022 is the year when AI will prove its mettle by offering near-term guidance, assisting sales and marketing with recommendations that they can choose to follow, and, over time as AI proves to be accurate and helpful, trust is established.
In 2022, top areas for the application of AI for sales-marketing-service include:
Lead quality analysis – i.e., likelihood of converting and closing
Nurture campaign effectiveness – i.e., attribution and adjustment
Probability of a lead converting, probability of a lead closing
Forecasting and pipeline analysis
Sentiment analysis for case handling, sales engagements, and next best actions
Next best actions overall
Anomaly detection – i.e., analyzing data to find the “interesting” bit that needs attention
Conversational AI – powered by bots – for anything from marketing engagements, sales qualification, and customer support
As AI helps organizations make better decisions and reduce blind spots, busy work, and roadblocks, AI in sales, marketing, and service will become more trusted.
From Paul Barba, Chief Scientist, Lexalytics, an InMoment company offering sentiment and intent analysis:
$100M Language Model - The race to train the largest possible language model continues unabated, and whether GPT-4 weights in at a particularly heavy parameter count or another of the tech giants reaches for this particular crown, an organization will announce a transformer-based deep network that cost at least $100M to train in 2022. Each generation of language models has shown improvements on standard tasks and occasional new behaviors, but with inference costs also ballooning with model size, the commercial use case will be limited.
AI Compliance Officers become key- With Europe preparing regulations on AI and America potentially not far behind, we're entering an era of AI regulation for businesses to follow. Especially in America, where patchwork rules will likely show up across state borders, following these rules will be complex and expensive, and a new set of job titles will be added to the corporate lexicon for this new compliance role. While heavily regulated industries like medicine and finance may find any AI specific regulations not particularly onerous compared to their current regulatory regime, many other industries will have trouble adapting and in particular finding individuals with both the technical chops to make sense of the technology and the legal chops to make sense of the rules. Those who can bridge both skill sets will gain entry to a fast growing and lucrative career track.
From Mehul Nagrani, GM, AI Product & Technology, InMoment, offering an enterprise feedback management platform:
Bias-Detecting AI. Teaching AI to recognize racism, sexism, and other forms of discrimination will become a standard part of the technology toolbox. 2020 and 2021 saw some notable progress in teaching deep learning models to not be discriminatory, but most of this work was in the academic sphere. In 2022 we’ll see this migrate to the corporate arena where models will be commonly deployed to identify inappropriate content.
Intentions Recognition as a High-Value Business Feature - Intention extraction (i.e., will a particular customer buy, sell, quit or recommend a product or service) have been available in some NLP systems for a few years now, but haven't become one of the standard features that everyone requests. As Customer Experience (CX) solutions become a bigger piece of a company’s IT landscape, intention recognition will become a must-have feature. Identifying customers that are about to cancel has tremendous ROI to a business, so intentions may become as important as sentiment.
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