The AI revolution | The future of business is wild

We're witnessing a paradigm shift in the nature of business, the future will be faster and more complex than ever imagined.

Here is the second of three articles with my thoughts on technology evolution, which in my opinion comes full circle to the need for us humans to adapt our own behaviours and professional development to thrive with the very technology we've created.

1. The data age | The exponential growth of data will change the world
2. The AI revolution | The future of business is wild
3. The evolution gap | The necessary human change required to thrive (coming soon)

The computer was born in 1944 when Colossus was built to crack Nazi codes. Since then, clever people worked their genius to make truly magical things happen. From less-than humble beginnings in warfare to wholesale adoption by business and every-day-people, machine intelligence has long played its’ small part in societal evolution. Now it is about to become pivotal. The world is on the brink of supersonic acceleration in the power and adoption of artificial intelligence. This impending reality requires urgent attention and we must all scramble to prepare for an onrush of innovation.

Today’s rapid change has several causes. One is the boom-to-boom economics of supply and [seemingly never-ending] demand. Most notably in the tech industry and the cosmic rise of consumer electronics. Small, inexpensive chips guide, support and engage us every day. The phones and computers we use, the cars we drive (and those that drive themselves) – even the very internet we rely on for almost everything we do.

In business, this equates to smart systems deployed to optimise operations. Scaling up a technology once confined to large enterprises. A second is the recent exponential advance of AI, enabling astonishing feats of data analysis and higher-order problem solving. A third is fierce rivalry between businesses in oversaturated segments, in which companies see AI as the key to market superiority and competitive advantage.

From automating routine tasks to evolving the value of an entire department, generative AI is already making the lives of professionals easier. Making the daily grind, less grinding.

The results are most visible in the advance of smart tech. AI-driven analytics and task automation have been vital to companies for optimising operations and enhancing user experience. AI’s role is as the solution to inefficiencies, enabling people to make more informed decisions, faster. Systems and their clever algorithms continuously pooling data and reviewing trends to surface predictions to the people ultimately responsible for execution.

AI vs. humans: primed to replace countless jobs

In the business of law, clever tech is drafting complex contracts and legal opinions, preparing lawyers for court, searching vast volumes of case law from all over the world, in multiple languages, to surface relevant precedents at superhuman speeds.

The truth is, I wouldn’t want to be a paralegal today.

The capabilities of Generative AI legal assistants bear resounding similarities to the job description of a typical paralegal. Is this an opportunity to empower paralegals to focus on alternative value added initiatives? Or, will it mean a whimpering end to a cornerstone of the legal profession? The same question can be asked of equivalent crafts across all sectors. Similarities can be drawn of the industrial revolution.

While the Industrial Revolution created economic growth, increased efficiency and offered new opportunities, that progress came with significant downsides; long-lasting damage to the environment and terrible conditions for workers. The latter leading to decades of riots, unionisation and mistrust between company and worker.

I wonder what the history books will write of the AI revolution?

Breaking the connection between humans and machines

The next evolutionary step is the most stark. Breaking the connection between human oversight and operational execution could soon let companies conjure-up and deploy competitive market strategies, in real-time, while their human-leaders are out the loop, blissfully unaware.

The 1990’s and 2000’s saw companies rush the gates (in Britain, we politely queued) to outsource and offshore call centres, as technology and costs allowed for truly global business operations.

The 2020’s and 2030’s will see companies rush the gates to outsource the design, development and delivery of their operations. This time, not spinning-out to low-wage geographies, but delegating command and control to AI-driven technologies.        

When it comes to commercial application, AI powers a suite of abilities for companies, the series of steps beginning with market analysis and ending in customer satisfaction. AI’s deeper significance is what it can do at a strategic level. Because it sorts through and processes data at superhuman speed, it can identify market trends out of a thousand data points or interpret customer behaviour to distinguish high-value opportunities sooner and more accurately than traditionally possible.

Eventually, self-directing smart systems will be designed to make the very decisions that today they are informing.

At a higher level, AI can solve much larger problems than those faced by a single business or department. Today that means simple tasks, such as determining the best marketing strategy for a new product. In due course, “decision-support systems” may be able to grasp the baffling complexity of global business environments, ever-changing regulatory landscapes and crafty competitor behaviours.

The consequences of this are only just becoming clear. AI systems, coupled with autonomous business processes, are likely to compute and execute opportunities at an unprecedented speed and on a vast scale.

The speed of such modern business operations will change the balance between people and software. Today, decisions are wholly made by humans, informed by systems. As strategic decision making is compressed into a new and faster ‘speed of business’, that balance will shift as leaders oversee the system without intervening in every action.

The paradox is that as AI gives a clearer sense of the business landscape, the art of doing business becomes more opaque for the people running companies. There will be less time to stop and think. As the models hand down increasingly prophetic judgments, their output will become ever harder to scrutinise without giving competitors a strategic advantage. Companies will fear that if they do not give their AI mega-systems a longer leash, they will be outpaced by rivals who do. This may favour established companies, which can leverage their resources of huge lakes of proprietary data, ripe for harvesting by the machinery of AI, while smaller firms struggle to keep up. But, there is always room for innovation. Agile newcomers will take bold actions to disrupt markets, take down incumbent players and establish market share. Where there is money to be made, innovations will be innovated. This goes for those nasty bad-actors too, devising ways to hack their way in where they're not wanted.

For every positive step you make in AI-powered business, there is an equal and opposite force seeking to compete against, disrupt or dismantle your operations.

Basic AI tools may get cheaper, but the systems that power, connect and protect business operations (and the ones that promise the best outcomes), will be fiendishly expensive. Building AI-infused enterprises will take huge investments in data governance, cloud infrastructure and data analytics. Training the models will call for access to vast troves of proprietary data. Proprietary data that companies will want to defend from equally AI-powered competition and hackers alike. And, regulators may argue isn't theirs to unleash AI upon in the first place.

The human-machine team

Culture matters, too. Today’s leaders have the task of mixing together clever people with clever AI-driven technology without really knowing how it will work out. To develop the strategy, governance and moral code to which their AI-driven operations will abide. While throwing out and re-writing the rulebook on human capital. With new ways of working, new roles and responsibilities, new methods to measure productivity (somehow business leaders still haven’t grasped the truth that measuring outcomes is much more beneficial than measuring output); to empower non-machine employees to provide value – and to feel valued.

Responsible AI

Already, regulatory frameworks are being pressure-tested. AI control over critical operations with low-human and no-human oversight will push them even further. Ethics play a crucial role in guiding the development and adoption of artificial intelligence, beyond simply regulation.

AI lacks a moral centre unless developed with one

In The data age | The exponential growth of data will change the world I discuss the imperative need to setting foundational principles of standards, data management and technology strategy. Essentially, developing a policy of ‘why’, ‘how’ and ‘when’ is the whole point, to define what a company stands for. The values and corporate vision from which every strategy, initiative and task should hang. An evolving set of principles that act as a company’s moral compass. To be used as a benchmark for a company to look itself in the mirror and temperature check [audit?] the company is adhering to its’ commitments when it comes to growth (profitability), regulation, brand values and social economic impact.

Never has it been so important for a company to define a technology philosophy when that very technology may be somewhat autonomously developing and executing strategy – on the company's behalf.

In crisis management planning, human-to-human communication will become more important than ever. Having a so-called off switch or override button. AI systems designed to operate autonomously and maximise business advantage will need to be hard-coded with values and restraints that human managers take for granted. These include placing an implicit value on ethical practices – how much market disruption is acceptable in pursuing a high-value opportunity? – how many customers is it okay to inconvenience when deploying an update? – and, avoiding certain overly aggressive actions in culturally nuanced markets.

Generative AI is driving at speed and without a break pedal to slow it down.

The uncertainties are profound. The possibilities are wild. The potential for misuse is serious. The only sure thing is that AI-powered business is the future. And, the future has arrived in style. The companies that anticipate and master this unchartered technological environment earliest and most effectively will probably prevail. Everyone else is likely to be left behind.