The future is closer than we think

Alison Blair headshot
Alison Blair, Director, PwC Research

It’s 2030 and a generation of super-workers – thanks to medical, technological and physical enhancements – inhabit a world where exceptional talent commands premium reward but where the number of workers in full-time permanent employment has never been lower.

This is a world with few rules, where specialists and niche profit-makers serve self-obsessed consumers and powerful affinity groups. A world where global corporates – some bigger than countries – coexist uneasily alongside small socially-responsible and environmentally-aware collectives.

And in this brave new world, data is the source of power. Consumer preferences, purchasing habits, corporate decisions, state investments – even the weather – are all interlocking digital information, sources to be mined, refined, valued and monetised in a million different forms. Regulators are data-focused and corporate and national courts are choked with claims and counterclaims over who owns, should own and profit from this data.

This is no sci-fi movie script – it’s part of a series possible future scenarios contained in a PwC report, Workforce of the future: the competing forces shaping 2030, which surveyed attitudes to the future of work among 10,000 people across the UK, Germany, China, India and the US (including 2,000 respondents in the UK). The future world of 2030 will be shaped by shifts in global economic power, depleted fossil fuels, extreme weather, water scarcity, a growing global population containing an ageing workforce – and data.

This, in turn, will create a landscape where digital platforms and artificial intelligence (AI) will underpin, define and shape the competitive workplace and its inhabitants. A far cry from our 2012 Business of Evidence report, which valued the UK market at around £3bn annually and suggested that the research industry, “…was already experimenting with technology and the early opportunities provided by data analytics.” And while we prophesied that the market would experience a “dramatic technology-driven expansion,” we could not visualise then what we’re contemplating now – a mere five years later.


The market intelligence firm, IDC, predicts that the annual ‘digital universe’ (that volume of data created and copied every year) will reach 180 zettabytes (180 followed by 21 zeros) in 2025.That’s some volume of data to push around the broadband spectrum and the data-masters know it. According to the Wall Street Journal, in 2016, Amazon, Alphabet and Microsoft invested $32bn in capital and leasing spend on data refineries in anticipation that more data will need to be moved further and faster in the future.

Then there is the quality of a new generation of data that is emerging from an increasingly connected world. It’s when your houseplants tell you that they need watering that you’ve come face to face with AI and the Internet of Things (IoT). Globally, it’s estimated that there are about 8.4bn smart phones, sensors, actuators, vehicles, cameras and drones now connected. That’s more than the world’s human population, but it’s a world where previously mute industrial machines exchange maintenance memos in real time, where tractors collect and communicate soil data and weather conditions to optimise agricultural production.


The road to 2030 will be signposted by dramatic step-changes in AI. We are already exploiting assisted intelligence – like automating repetitive tasks; we are close to breakthroughs in augmented intelligence – where humans and machines collaborate; and by 2030 this will culminate in a world of autonomous intelligence – where adaptive intelligent systems take over decision-making based on huge advances in machine learning that are already delivering frighteningly high levels of predictive accuracy.

Machine Learning (ML), is the extension of AI based on the notion that we should really just give machines access to data and let them learn for themselves. When Amazon suggests items you might like based on previous purchases, when brokers make investment decisions based on market trends and when mechanical devices are shut down to prevent failure, they’re all using some level of machine learning. Ultimately, the ability to capture data, analyse it, personalise shopping experiences, implement tailored marketing campaigns and determine stock levels is retail nirvana – but it’s on the way. Already we see tailored offers sent to our phones on entering many high street stores and digital mirrors moving towards offering us the ultimate shopper experience.

For researchers, that future is challenging. IDC, among other industry researchers, predict that half of all business analytics software will include the intelligence where it’s needed by 2020. In addition, real-time streaming of insights into data will be the industry goal, according to Forrester. Its prediction for the near future is that data science, real-time data capture and analytics will close the gaps between data, insight and action. That further reinforces machine learning as a top strategic trend, becoming a necessary element for data preparation and predictive analysis in business, while, for many businesses, the link between cognitive computing and analytics will become synonymous in much the same way that businesses now see similarities between analytics and big data.


How does all this impact the future of the research industry? If we couldn’t predict today’s AI environment five years ago, it’s even more difficult to predict the shape of the industry by 2020, let alone 2030. Last year’s Business of Evidence 2016 report told us that two thirds of our industry adapts quickly to developments in new technology, but that technology-based skills shortages were rife and that wearables and neuroscience were the fast emerging methods. But the emerging trends and focus of investment today is towards integrating data, analytics, insight and outcomes. Organisations will increasingly look to making real-time decisions from real-time analysis of an array of data sources – but one trend may be that, increased sophistication of software means more being done in-house.

We also see that the ‘data lakes’ that now exist are more than ever in need of a layer of insight and understanding. Data can predict how we might act, behave or respond but the need to engage with people to understand why continues. This area too has seen fast moving developments, for example in the use of Virtual Reality (VR) to reimagine the capabilities of what can be achieved in observation research. Instead of simply observing, businesses want to know the reasons behind every decision that a consumer makes. VR presents an opportunity to study an audience in greater depth than ever before and in a more cost effective manner and a greater enhanced user experience.

Last year we said that fresh thinking and courageous leadership, combined with a dose of optimism was key for the industry to shake off the shackles of the analogue past and embrace the digital future. This year, we’d repeat that and merely add that getting to grips with AI and ML should be in everyone’s New Year resolution list.

To see the latest edition of the Research Live Yearbook, click here.

By Alison Blair, Director, PwC Research ([email protected]).

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