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Human ingenuity is the key to helping restart our economies

In order to respond to the unprecedented impact of the pandemic, we will need our economies back on track, delivering goods and services essential for our health, wealth and well-being. Firms, more than ever before, will need to step up to provide a service to society. But with the ground rules changing under their feet, organisations of all kinds need to be adaptable and resourceful in contending with these new realities. This will require human ingenuity, enabled by technological innovation and Artificial Intelligence (AI) will play a big part in this.

The pandemic has impacted almost every business. Indeed, it is hard to imagine any business that hasn’t been forced to contend with this shock. What is remarkable is how rapidly, in a matter of days, many organisations have risen to this challenge. Schools, such as my daughter’s, have used tools like Microsoft Teams to flip into remote learning for hundreds of students. Banks have moved thousands of loans to small businesses using the Internet alone. Doctors are seeing patients by video rather than in person. Seemingly, a decades’ worth of change has happened in a couple of weeks.

But this isn’t the end of matters. What we have seen, admirable as it is, is merely the reflex response, the organisational adrenaline, the first act. Everyone is bracing for a period of instability, uncertainty and also novelty. The environment will continue to change as governments figure out the guardrails for reopening the economy safely. And during this time companies will have to continually adapt.

Technology will play a role in this, without question, as it did in act one. Technology investments, particularly those in AI, have supported key corporate priorities, such as streamlining business operations or improving the customer experience.

But for companies, as it is for communities, this process of adapting to the unknowable is more than just about technology. It will be the combination of human and machine that will get us there.

Past ways of doing things may not be as useful a guide as before. Analytics, including predictive analytics, which can help employees identify new customer behaviours will be essential to the ongoing process of rethinking.

Firms will need to draw deep on the resources of their employees, their ingenuity, empathy and judgement to help with both adaptation and recovery.

This impetus towards ongoing adaptation seems true across sectors. I’ve spoken to senior leaders in finance, media, apparel, professional services, transport, healthcare and other industries. Even though the specifics of their challenges are different, every sector faces a short-term adaption and long-term redesign conundrum.

Customer needs will change. More customers will expect digital delivery of services and automated interactions. Just one example: call centres. If physical premises re-open but need to implement distancing measures, large parts of any given shift will be working remotely. Given the difference in load, automated customer services via voice or text may become essential in scaling up customer interfaces. (For example, Microsoft, CDC Team Up on Chatbot to Check for Coronavirus Symptoms)

Supply chains are adapting. Employees and executives will need better information about where goods are and where they are needed, and the ability to predict how to match demand with possible supply. Understanding, analysing, predicting and tracing items flowing through the supply chain will be critical if lockdowns become more frequent. Decisions will also need to be made about manufacture, and how to add resilience with automation. (See my discussion with Pamela Mar on the Future of Digital Supply Chains).

These are all problems of increasing complexity, and any subset of these changes might have involved a major transformation project in the past. Today there is an urgency to adapt in a matter of weeks. What is more, the goalposts will continue to move over the coming quarters. There is no single change. Rather firms will need to stay on their toes and continuously adapt as local policies change, customer behaviour shifts and new information comes to light. Once and done, this isn’t.

So, within a given sector, which types of firms are more likely to be able to understand and then adapt their operations? Which firms, in other words, have the capacity for ingenuity, agility and adaptability? And what characteristics will help them do so continuously?

Microsoft’s global research study on AI & skills conducted in March suggests that AI-leading firms, because of the maturity of their adoption and the contribution AI programmes make to their business, are more likely to have the capabilities needed.

Why? It isn’t simply the technology investment made by these firms, although clearly that helps.

Those firms that gain the most effective benefits from AI have also invested in skilling their employees and building a positive, innovation-oriented culture. It is that human capital in tandem with AI technologies that is the magic mix.

AI-leading firms have put many more resources than others towards skilling their employees in higher order technical and problem-solving skills. They have also invested in tools which augment the skills of their employees.

Consequently, they have an ‘innovation dividend’ which, in the past was a predictor of higher growth and would today presage, I believe, better adaptability in the face of many crises.

When we look at how AI is applied in firms at different stages of their AI journey, this conclusion becomes stark. When it comes to using AI to make operations more efficient, AI-leading firms have a minor advantage over laggards. However, when it comes to improving customer experience or innovating through the delivery of new services, AI-leaders are twice as likely as the least mature segment to benefit from applying these breakthrough technologies. (See chart below)

But here is something that I found particularly telling. AI-leading firms seems to have fostered a virtuous cycle, between AI investment and upskilling, which allows them to cement their lead over slower moving firms. Their leadership in AI results in:

– Successful AI projects, leading to demand from across the organisation to use more AI technologies (Microsoft’s research identifies that 84% of AI-leading firms claim to get value from AI, compared to 59% of businesses at an early stage in their AI journey);

– The increasing skill levels in employees creates a more motivated and engaged workforce, keen to use more AI tools and continue to strengthen those skills;

– This fosters a more vibrant culture;

– Creates a willingness to broaden these new approaches across the organisation, leading to more success.

Such virtuous cycles sow dividends that reap yet more. For AI-leaders, this puts them ahead of laggards in three key dimensions:

– They have done more and moved more quickly to acquire and deepen a wider range of skills from data and analytics, to collaboration and higher order collaborative working (94% of AI leading businesses are actively building skills or have plans to, and two-thirds of their employees already been part of reskilling programs);

– They are better at using AI technologies to augment the skills of their employees (Amongst AI-leading businesses, more than 84% of senior executives and 62% of employees say AI supports and enhances their roles);

– They have a more innovative culture which has resulted in improved products and services and, historically, a higher likelihood of double-digit growth.

For firms less far along their journey than these leaders, one key question must be tackled. How can we create and sustain this virtuous cycle? In tough times, firms will need to dig deep and consider two things: The first is to apply AI into areas with more strategic or customer value, rather than focus exclusively on efficiency. The second is to complement those technical investments with investments in human capital, which represents the second part of the flywheel.

As we continue to adjust from the shock of coronavirus, few firms have the choice to return to business-as-usual. The old baseline has been written off. For many firms this will require changes in operations and products, novelty rather than optimisation. To successfully tack into that, a combination of human ingenuity and leveraging technology, underpinned by a focus on skills, may be required.

Azeem Azhar is an AI industry expert and founder of the Exponential View