6 AI trends that will define 2022.
AI is no longer just the domain of data scientists and mathematicians. It’s becoming applied. Powering more efficient operations. Automating processes. Delivering better customer experiences. And it shows. 52% of companies accelerated their AI adoption plans in the last 18 months, according to PwC, and AI startups around the world raised $50bn across more than 2,000 deals last year – surpassing 2020 levels by 55%.
This momentum will only ramp up in 2022 and beyond. For one, AI is industry agnostic; all businesses are now data businesses, and AI makes that data more powerful. Whether it’s informing new product features or reducing the cooling bill of Google’s data centres. Second, it’s helping to meet the expectations – fast, personalised digital experiences – of generation Z (anyone born from 1997 onward), now the biggest population cohort. And finally, it has the potential to scale products, services and internal processes without an increase in headcount. Not a straight replacement for people, but a catalyst for more efficient and meaningful work.
Here are the trends and applications in AI, machine learning and automation that we’re most excited about in 2022.
AI-assisted content creation
AI is already finishing our sentences – now it’s ready to finish paragraphs and articles. Or as Frase’s free AI rewriting tool preferred it: “Artificial Intelligence (AI) has been helping us write for years; now it’s time to help us write entire articles!”
Most AI content generators use large language models like GPT-3, which are trained on billions of web pages and behave like text auto-completers – you feed them a prompt and they predict what text should follow.
Frase, for instance, uses its own proprietary AI model to help marketers and content creators generate briefs and outlines based on nothing but a title, rewrite paragraphs, identify the keywords and metadata you should include in your content, and compare your content’s keywords against those of your top competitors. AI becomes both the facilitator and guardian of your business’s tone of voice and style.
While it’s not going to replace human writers anytime soon, it will make their job easier. Writers will increasingly become editors as they riff off the output of the AI.
And this is just part of a larger trend of AI-assisted creation – from generative art to auto-completing code. Sourcery, the London based AI code assistant suggests improvements while a developer is coding, in real-time. The software cleans their code, reduces technical debt, and instantly refactors so they can get more done. Sourcey is being used by over 7000 developers at household brands including Sky, Microsoft, Amazon, and LinkedIn. Here at Forward, we recently led their seed round of £1.75M, and will be working closely with the team to help them scale.
AI and machine learning will drive the increased personalisation of learning in 2022.
Duolingo, the app which helps more than 300 million people learn new languages, uses its enormous data trove to power everything from optimising reminder notifications to figuring out how to help improve outcomes for learners of indigenous languages.
AI-powered personalisation will be their big play for 2022. The company’s working on a next-generation knowledge model internally referred to as Birdbrain 2.0. This new model will incorporate natural language processing – the ability of a computer to understand, analyse, manipulate, and potentially generate human language – to make even better predictions about what students know, helping to create fully personalised journeys for each learner.
Within our portfolio, Up Learn uses AI and cognitive science to help A-Lever students achieve better grades. They report that 97% of students who complete a course attain A*-A, by combining their technology with a network of trusted, vetted teachers. Their AI powered platform tailors the learning to the specific needs of the student, who have described using Up Learn as “like watching Netflix, but for education.”
But this will also have implications for talent acquisition and retention in 2022 and beyond. With the “Great Resignation” precipitated by the pandemic, providing more personalised progression and development is a must if you want to keep the best talent. AI-powered learning tools could identify potential roles for employees to move into and then generate a tailored learning route to help them get there. This is all the more important now as people follow less traditional educational and career routes, with 43% of candidates today being self-taught in one or more of their role’s requirements.
AI has been part of the ecommerce experience for years – we’ve all been exposed to AI-powered recommendation engines – but the beneficiaries were generally large businesses with big data teams. Now, AI tools are being put in the hands of merchants both great and small.
Shopify, for example, is deploying AI in its fulfilment network to predict the closest fulfilment centres and optimal inventory quantities per location to ensure fast, low-cost delivery of their merchants’ goods. Their business chat app, built with natural language processing, helps merchants convert conversations into sales. And, using machine learning models to predict merchant business success, the company can automatically send its merchants funding offers without them having to apply.
In addition, a host of third-party apps that integrate with Shopify are using data to provide AI-powered tools that help merchants optimise the full buyer journey, from marketing and conversational automation, to recommendations and cart abandonment.
It’s helping merchants convert, but also delivering a more accessible, seamless and personalised digital shopping experience for buyers. We now expect more from retailers, and AI is helping merchants of all sizes meet those expectations – from targeted product recommendations to faster shipping and better ways to connect. Through our work with eComm founders at Forward Advances, we’ve seen the remarkable difference AI can make at every stage of growth. From marketing campaigns, to search results, through to the checkout experience.
No-code AI and automation
With 48% of CIOs reporting that they’ve already deployed or plan to deploy AI and machine learning technologies within the next 12 months, the demands for specialised talent will far outweigh supply. And what do companies without specific data science teams do?
Platforms that allow anyone in a business to build and deploy machine learning tools or automated services with simple drag-and-drop functionality – so-called low- or no-code technology – will take centre stage in 2022 as businesses both big and small race to deploy AI-powered tools.
It means faster implementation and a reduction in costs, because there’s no need to write or debug code, and no need for a specific data science team. And, most importantly, it puts product development in the hands of people who are closest to the pain points and customers. They can focus on putting out something that works and get results – and then iterate rapidly.
No-code technology empowers lawyers, marketers, accountants, recruiters to build, customise and deploy data-driven products themselves, making it easier to build solutions that their customers really need fast. James Clough, Co-Founder and Chief Technology Officer of Robin AI notes, "AI allows time-consuming and routine legal tasks to be automated so that legal experts can focus efforts on where they can best add value using their own experience and judgement. Rather than replacing people from the process, AI allows people to specialise in areas where their expertise is most valuable while technology handles the rest."
Rise of synthetic data
In 2022, businesses will increasingly turn to synthetic data generation – data not collected from the real world, but generated by an algorithm. By 2025, Gartner expects generative AI, which can generate synthetic data, to account for 10% of all data produced. That’s up from 1% today.
Baidu’s Apollo, for example, is already creating synthetic datasets with which to train autonomous vehicles in a simulated world, where the consequences of something going wrong are minimal. It’s also increasingly being used in health care, where synthetic data can mimic real health data without patient-privacy concerns. This will enable researchers to spin up studies much more quickly, which is vital in the face of events like Covid-19.
Data gathering and management has always been a thorn in the side of businesses, and all the more so with the increased use of data-hungry technology and byzantine data protection laws. Synthetic data lets businesses focus on quickly generating realistic dummy data sets for product development, health care and prediction models, without worrying about patchy data or privacy issues.
All of these trends and applications, however, depend on getting the data fundamentals right. While businesses are experimenting with AI, many are struggling to make it part of their standard operations or deliver real, sustainable value with it.
AI, machine learning and automation that delivers relies on good, clean data that’s readily accessible. For that reason, 2022 will see businesses turning inwards to create the infrastructure needed to efficiently move data throughout their organisations. Indeed, 62% of respondents to the 2021 Appen State of AI report were using AI to support internal operations, making it the number one use case of AI. 2022, then, will also see the continued rise of AI- and ML-ops companies as businesses deploy data fabric architecture – integrating data across a business’s many platforms and users – to eliminate silos and manage data throughout the AI life cycle.
It’s going to be a big year for AI, machine learning and automation, but the game will go to those businesses that first get their data houses in order, laying the foundations to take full advantage of these applications and trends.
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