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AI will drive 300 years of change by 2026 as blue and white-collar workers vanish, says Avanade

Chris Middleton Profile picture for user cmiddleton October 20, 2023
Summary:
Avanade predicts a wholesale transformation of business in three years. But is it more techno-evangelism, or is there a basis in fact?

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In the next three years, AI will create 300 years of change, plus a new generation of 'no collar' workers. That’s the bold claim of Avanade, the 23-year-old joint venture between Microsoft and professional services giant Accenture. 

The company predicts a near future where traditional distinctions between blue- and white-collar jobs are swept aside by AI co-pilots. The result will be more jobs for human workers, rather than the mass unemployment predicted by some commentators. 

But is this simply another utopian vision from a vendor – a fantasy to counter the dystopias envisaged by those who fear AI’s impact?

Florin Rotar is Chief AI Officer at Avanade, a new role for the company veteran who was its first European appointment, long before it grew to 65,000 employees in 26 countries. He says:

We fundamentally believe that, in the next three years, the nature and the fabric of work are going to change more than in the last 300 years combined. We’re going to see 300 years’ of transformation.

The truisms that we have all believed since the Industrial Revolution, about the nature of organizations and mid-level management, all that will change in the next three years. The notion of blue-collar and white-collar workers is going to disappear. Instead, we will have ‘no collar’ employees: people who are collaborating with an AI co-pilot. 

So, it's not about AI replacing jobs or replacing humans, because humans will still be the pilots, so to speak, for the foreseeable future. They will have a superpower enabled with AI, with whom [sic] they are going to continuously communicate and collaborate.  The AI helping the human, and the human helping the AI in a constructive and beautiful symbiosis.

Language like this certainly sounds utopian – techno-evangelism of a type that sounds closer to marcomms or political grandstanding than strategic consulting - but Rotar tempers his point with an interesting observation:

We've got to make certain that we don't make the same mistakes of the past 100 years, where we create divisions between enabled and ‘unable' people. The enlightened customers we work with are not thinking about AI as just ‘more productivity and automation’. They're truly thinking about how to help people become the best versions of themselves.

An enticing idea. Yet surveys about AI, automation, and ‘Industry 4.0’ adoption in recent years have tended to find business leaders more determined to slash costs and do more with less than invest in ‘superpowers’ and employee betterment. Rotar responds:

Well, I'm not a hippie. I mean, we live in the real world, right? The economic climate changes, and management changes, but technology changes even faster. But I think the realization now is that, to get the business benefits and outcomes you want – to truly increase your chances of success – you have to take people with you. And if you truly empower your people, then it becomes a more efficient journey. Including in realizing cost reductions and getting efficiencies, if that's your primary goal. 

He adds: 

I believe AI now is giving us the opportunity to make this an ‘and’ world, rather than an ‘or’ world. You need the uplift in top line, the increase in revenue and profitability, but you do that with AI-powered people enablement.  So, you can have your cake and eat it! That’s one of the fundamental changes that AI brings to the table. You don't need to choose between people and money.

Evidence

But is there evidence that this is actually happening? Yes and no, according to Avanade’s own research. 

For its AI Readiness Report, published this week, the company surveyed 3,000 business and IT leaders in medium-to-large enterprises in Banking, Energy, Government, Health, Life Sciences, Manufacturing, Non-profit, Retail, and Utilities – all organizations with annual revenues of more than $500 million.

On the one hand, it found that nearly two-thirds of respondents (64%) believe that adopting AI will either maintain or increase their workforce next year, with a majority of those anticipating a headcount increase of up to nine percent. 

So, more jobs, not fewer – albeit in the short term. A longer-range forecast is nowhere to be seen, largely because no-one knows what the long-term repercussions will be.

However, nearly as many (63%) said their employees will need new skills – and in many cases, a completely new skill set, as enterprises switch to the ‘AI-first operating model’ predicted by a staggering 92% of respondents. A transformation they believe will take place in 2024.

But are those leaders – the majority of Avanade’s survey base – simply being seduced by vendor hype rather than a desire to fulfil real business needs? This question may prove critical, given that less than half (48%) of organizations have put in place policies for responsible AI adoption – down from 52% in March. Hard evidence of collective irresponsibility?

Meanwhile, roughly half of respondents “admit they do not have the utmost confidence that their organization’s risk management processes are adequate for an enterprise-wide technical integration of generative AI”, adds the report.

All of this suggests a tactical rush to adopt AI – largely to keep pace with others who are doing the same – rather than a top-down, strategic process that solves real problems.Not a bit of it, says Rotar:

That was the case maybe nine or 12 months ago. There were loads of experiments triggered by ChatGPT, and so on, which democratized people's imaginations about what you could do with AI. But in the last six months, they became organized projects, valuable use cases, pilots, and prototypes about how to use generative AI in a safe, secure, scalable, reliable way. And in the last three or four months, our experience has been that it has now become a board- level, C-suite topic. 

Those prototypes have gone into project deployments at scale, and in mission-critical environments. Now a number of industries are truly thinking about – and planning for – how to transform an entire function, redefine lines of business, and in some cases redefine their whole industry.

As for examples to back this up,  Rotar says:

Knowledge-heavy industries are leading the charge: professional services of all kinds, whether it's financial advice, lawyers, or consultants. Avanade has been on that journey too, disrupting and changing ourselves for almost a year.

Media and entertainment is another industry that is moving really fast, because its lifeblood is content. Financial Services, is, in many cases, leaning forward as well. But I'm also seeing a tremendous amount of work in industries that you might not think of as being so forward-looking, such as Energy and Utilities.

He cites a specific case in point: 

An oil and gas giant [client of Avanade’s] operates huge installations and refineries. For years, it has been using traditional AI with predictive analytics to figure out when things might go wrong. But what generative AI offers is the next step, the ‘so what?’ question: if there is a defect, how do you repair that? 

They are deploying AI-powered knowledge management, which is reasoning on top of a quarter of a million unstructured and semi-structured documents, articles, and handbooks, and combining that with structured data from line-of-business systems.

In terms of other use cases Avanade is seeing among its customers, Rotar argues: 

It’s about knowledge finding and management. Helping connect the dots between structured, semi-structured, and unstructured data, reasoning on top of hundreds of thousands of documents, data points, and line-of-business systems, then combining that with the power of a Large Language Model.

This gives people a ChatGPT-like experience, he suggests, but using trusted corporate data, rather than content scraped from the pre-2021 internet. It can also help internal processes become more efficient, he adds:

A bank that may be receiving 100,000 letters a month, including correspondence from the Financial Ombudsman, customers, suppliers, regulators, and so forth, needs to read all of those letters and respond to them appropriately. That’s absolutely a sweet spot for generative AI. 

Another use case that’s becoming more common is customer service and support, putting the gen AI superpower in the hands of the people who work in stores, branches, and contact centres to better service customers. 

And another is software engineering, using AI to transform and accelerate the software development lifecycle. Those are the main use cases we see, but the most forward-leaning organizations are already moving beyond that. They’re looking at using AI to fundamentally transform their business.

But...

More bold words, given the dearth of training and board-level understanding identified by Avanade’s own findings. The report, is far from as positive as Rotar seems to believe. It says:

Only 36% of CEOs say they are very confident about their leadership’s understanding of generative AI and its governance needs today. Our research suggests a wide gap in the level at which organizations are prioritizing the outputs of the AI technology versus the necessary investments in people that must also be made. 

Only 52% say their organization has complete human capital and workforce planning processes in place to safeguard roles as generative AI is scaled. Doubts also emerge when it comes to AI risk and responsibility. About half (49%) are not fully confident that their organization’s risk management processes are adequate for an enterprise-wide technical integration of generative AI.

Meanwhile, as noted, less than half (and falling) of business and IT leaders say their organization has put in place responsible AI guidelines.  Set in the context of most medium to large enterprises (92% of them, in Avanade’s research) moving to an ‘AI-first’ approach in the immediate future, this suggests that many business and IT leaders are locked into troubling herd-like behaviour, with too little consideration of the internal – and external – impacts.

Rotar acknowledges that the gaps between an organization’s desire for AI, and its ability to implement it responsibly, need filling:

When you have responsible AI adoption, and people-first usage, the approach should be ‘how do we make the more junior people feel appreciated, more empowered, and accelerate their careers?’ 

Having an AI ethicist involved in training and evolving those models – to do the right thing – that’s a win-win for everybody. And the people who've been there for a while, they have a responsibility to be mentors, as guardians of the AI models which are being used. AI ambassadors.

Avanade’s own ‘School of AI’ is actively training all 65,000 employees, says Rotar. But is he concerned that organizations are, too quickly, putting their future in the hands of machines, when the long-term repercussions of doing so are completely unknown? An active policy that may leave humans as little more than passive users, and passive receivers of information from uncertain sources?

He responds:

We're trying to teach people not to fall into that trap. As an individual, you're in control. You are the pilot. You have an AI co-pilot, but the pilot is responsible and accountable. You have to be awake at all points in time. You have the responsibility of the judgement calls. 

A fundamental tenet of the training we're doing is to help people understand both the power and limitations of AI – to be a critical thinker. To understand their accountability and responsibility, so they don't fall asleep in the pilot’s seat.

There is a fundamental knowledge uplift which needs to happen. It’s about organizational readiness.

My take

On the latter point, wise words indeed. 

But Avanade’s evangelism and enterprise knowledge aside, I would argue that leaders’ apparent desire to put AI at the apex of their organizations so quickly is troubling, especially when combined with the stark lack of readiness revealed in the research. Not to mention the falling levels of responsible-AI training.

In this sense, 2023 may either mark the point at which business became smarter, or leaders collectively lost their marbles in a tactical rush to compete. It all comes down to who’s in the pilot’s seat.

Is it you?

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