Business Lookahead: jobs, prices and AI

From U.S. jobs numbers that could give the Fed pause for thought, to signs the AI bandwagon is picking up speed, these are the big stories to watch out for in business and finance in the coming days. Rachel Faber has the details

From key U.S. jobs figures, to the AI boom gathering pace, these are the business and finance stories to watch out for in the days ahead.

Investors hope U.S. employment numbers on Friday will come in just right… strong enough to suggest there won’t be a recession, but not so strong that they force the Federal Reserve into another big rate hike.

The forecast is for a gain of 180,000 jobs.

Thursday’s eurozone inflation numbers will stoke a debate over whether the ECB is likely to raise rates again.

Stubborn price rises have led some to think more increases are still to come.

HSBC predicts rates will peak at 4%, up from today’s 3.25%.

Hopes are fading for signs of an upturn in China’s economy.

Closely watched purchasing managers’ indexes aren't expected to change the mood, following a slew of dreary data.

After a slump in sales at Lenovo, hit by the fading of the work-from-home boom, we’ll get more clues about the health of the PC market.

Earnings are due from U.S. rivals Dell and HP during the week. And the AI bandwagon shows no signs of slowing down.

Forecast-smashing numbers from chipmaker Nvidia have only stoked the excitement.

It said it was benefiting as its chips were used for AI products like ChatGPT.

Generative AI for everyone

Imagine every employee in your company had an assistant that "knew" everything your organization had ever known—the entire history, context, nuance and intent of the business and its operations—and could process, analyze and use that information in a matter of seconds, in infinitely repeatable ways.

We're at a phase in the adoption cycle when most organizations are starting to experiment by consuming foundation models "off the shelf." However, the biggest value for many will come when they customize or fine tune models using their own data to address their unique needs.

Consume

Generative AI and LLM applications are ready to consume and easy to access. Companies can consume them through APIs and tailor them, to a small degree, for their own use cases through prompt engineering techniques such as prompt tuning and prefix learning.

Customize

To increase the value of generative AI and foundation models in specific business use cases, companies will increasingly customize pretrained models by fine-tuning them with their own data—unlocking new performance frontiers.

A look ahead at the fast-paced evolution of technology, regulation and business

The coming years will see outsized investment in generative AI, LLMs and foundation models. What’s unique about this evolution is that the technology, regulation, and business adoption are all accelerating exponentially at the same time.

The technology stack

Each layer of the generative AI tech stack (applications, fine-tuning, foundation models, data and infrastructure) will rapidly evolve – as the technology matures and as the compute demands grow exponentially. Cost and carbon emissions are central considerations in adopting energy-intensive generative AI.

The risk and regulatory environment

ChatGPT raises important questions about the responsible use of AI. The speed of technology evolution and adoption requires companies to pay close attention to any legal, ethical and reputational risks they may be incurring. They will have to answer key questions on intellectual property, data privacy and security, discrimination, product liability, trust and identity.

The scale of adoption in business

Companies must reinvent work to find a path to generative AI value. Business leaders must lead the change, starting now, in job redesign, task redesign and reskilling people. Ultimately, every role in an enterprise has the potential to be reinvented, once today’s jobs are decomposed into tasks that can be automated or assisted and reimagined for a new future of human + machine work.

ChatGPT’s explosive global popularity has given us AI’s first true inflection point in public adoption. Finally, everyone, everywhere can see the technology’s disruptive potential for themselves.

The large language models (LLMs) and foundation models powering these advances in generative AI are a significant turning point. They’ve not only cracked the code on language complexity, enabling machines to learn context, infer intent, and be independently creative, but they can also be quickly fine-tuned for a wide range of different tasks.

This technology is set to fundamentally transform everything from science, to business, to healthcare, for instance, to society itself. The positive impact on human creativity and productivity will be massive.

Companies will use these models to reinvent the way work is done. Every role in every enterprise has the potential to be reinvented, as humans working with AI co-pilots becomes the norm, dramatically amplifying what people can achieve. Generative AI will impact tasks, not occupations. Some of those tasks will be automated, some will be transformed through AI assistance, and some will be unaffected.

We can also expect a large number of new tasks for people to perform, such as ensuring the accurate and responsible use of generative AI systems. It’s why organizations that invest in training people to work alongside generative AI will have a significant advantage.