What does ChatGPT, the "fastest-growing consumer application in history," mean for the future of work? More broadly, will generative AI soon graduate from the being the latest consumer entertainment to become a significant business application and a new basis for competitive advantage? And are enterprises ready for AI, any type of AI? Forrester just published a report on generative AI that tells its enterprise clients not to ignore or downplay its impact. Enterprises should start right now to experiment with generative AI, recommends Forrester, focusing on existing processes that can be enhanced by technologies "that leverage massive corpuses of data, including large language models, to generate new content (e.g., text, video, images, audio, code)." It would be "a costly mistake," says Forrester, to ignore the potential of generative AI to enable production of content at scale, to accelerate the speed and precision of data science practices and app development, to produce synthetic data for training AI and machine learning models, and to provide new defense opportunities for security professionals. In short, generative AI presents an opportunity to augment and even automate existing work processes in IT, marketing, customer service and other business functions.

Towards the end of last year, management consultant McKinsey published an article where the first paragraph was created by ChatGPT, the generative artificial intelligence (AI) language model. The article's authors admitted that the AI's attempt was "not perfect but overwhelmingly impressive". They noted that products like ChatGPT and GitHub Copilot take technology into realms once thought to be reserved for humans. "With generative AI, computers can now arguably exhibit creativity. They can produce original content in response to queries, drawing from data they've ingested and interactions with users," they said.

December 1, 2022McKinsey has been named a Leader, the highest designation, in The Forrester Wave: AI Service Providers, Q4 2022 report. Forrester evaluated 12 firms, assessing them on 29 criteria grouped into the categories of current offering, strategy, and market presence. We received the highest possible rating in criteria including AI talent, vision, and market approach. "McKinsey & Company leads enterprises with end-to-end AI transformation," the Forrester report notes, also recognizing that "McKinsey addresses AI holistically: as a technology, an operational model, and a strategic asset." The report also notes that McKinsey "[places] a heavy emphasis on ROI." McKinsey acquired the AI arm of our firm, QuantumBlack, in 2015, and the Forrester report points out that this move "continues to deliver top-notch data science talent."

The world is a very different place than it was ten years ago, and nowhere is this more evident than in healthcare. The aftermath of the covid-19 pandemic, combined with the financial downturn and an acceleration in the adoption of technology and digitization, have dramatically changed the landscape for everyone, patient or practitioner. Here's my overview of what I believe will be the most important trends of the next 12 months: The market for Artificial intelligence (AI) – specifically, machine learning (ML) tools in healthcare is forecast to top $20 million in 2023. Various AI-aligned technologies, such as computer vision, natural language processing, and pattern recognition algorithms, are already deeply embedded in the healthcare ecosystem and will continue to be adopted as evidence of their usefulness grows throughout 2023. Some examples of areas where AI is used include drug discovery, where it can assist with predicting outcomes of clinical trials and potential side effects of new drugs, as well as analysis of medical imagery, which involves using computer vision algorithms to spot early warning signs of disease in x-rays or MRI scans.

Experts weighed in on leading with next-generation AI during a keynote panel at research and advisory company Forrester's Data & Strategy event this week. How is AI at work today? Michael Finnerty SVP, marketing solutions global services of identity resolution company Neustar, A TransUnion Company, talked about how companies are using AI to better understand and meet the needs of their customers. Chris Twogood, senior vice president, global marketing at software company Teradata Corporation, offered an example of how a large North American healthcare company is using AI to predict renal failure. AI has myriad use cases, but many companies are still in the early stages of adopting this technology.

Tis' the season – not just for holiday decor and annual family gatherings and celebrations – but for the business world's other sacred tradition: expert predictions for the year to come. These predictions are, of course, not a perfect science. If the last three years taught us anything, it should be to expect the unexpected (or should I say, the'unprecedented'). Nonetheless, it's best practice for businesses, especially those with a consumer-facing offering, such as hospitality providers and retailers, to not only reflect on the learnings of the year past but prepare for the predicted demands of the year ahead. This annual practice is especially important when we look at the technology landscape; after all, the continued embrace of technological innovation is, in many ways, a primary marker of success in our digitally-driven world.

Such exercises are always interesting but also inherently risky – particularly in uncertain times such as those we have recently experienced and continue to live through. Learn about the leading tech trends the world will lean into over the next 12 months and how they will affect your life and your job. For example, few at the end of 2019 would have forecast that the world of work would be turned upside down during the following year by a global pandemic, leading to an unprecedented focus on devices and services that facilitated remote working, and ushering in a likely permanent shift to a hybrid model. Then, just as economies were adjusting to and recovering from the pandemic, Russia's invasion of Ukraine in February 2022 caused a sharp rise in energy prices, increased inflation, supply chain issues and fears of widespread recession. This series of shocks has profound implications for the IT industry that look set to continue through 2023 and beyond.

Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Forrester Research's recently-released predictions report for artificial intelligence highlights what most have already observed: AI adoption has evolved from an emerging, nice-to-have trend to experiment with to a legitimate, must-do priority for enterprises. Basically, get on board the AI train or be left behind. The "get on board with AI now" message has been hammered home for several years, but this year's stats do seem to point to a significant evolution: According to Forrester's Data and Analytics Survey, 2022 [subscription required], 73% of data and analytics decision-makers are building AI technologies and 74% see a positive impact on their organizations from the use of AI. No vertical industry is failing to find opportunities to implement AI, and companies at all maturity levels are transforming fundamental functions in the organization, the predictions report found, while in 2023 AI adoption will "continue to expand and be more creative, trustworthy and optimized."

Audit analytics, procure to pay, order to cash and financial planning are four finance and accounting (F&A) processes where the AI technology required to elevate the process already exists. There is also an active community of technology providers and customer references indicate strong progress. Forrester gives these four use cases strong scores for adoption, such as a manageable skills gap, stable data and clear-cut business outcomes. Starting with audit analytics, auditors tend to spend too much time buried in compliance checklists and creating reports that few people read, with little time to seek anomalies in every transaction. Rather than manually sampling data points, Forrester says machine learning is being used for risk assessment of transactions.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Consolidating their organization's tech stacks, defending budgets and reducing risk are three of the top challenges facing CISOs going into 2023. Identifying which security technologies deliver the most value and defining spending guardrails is imperative. Forrester's 2023 security and risk planning guide provides CISOs prescriptive guidance on which technologies to increase and defend their investments and which to consider paring back spending and investment.