Businesses that successfully apply artificial intelligence could increase profitability by an average of 38 per cent by 2035, according to Accenture.

The consultants predict the introduction of AI could deliver an economic boost of US$14 trillion in additional gross value added (GVA) across 16 industries in 12 economies.

The figures are contained in a new report, How AI Boosts Industry Profits and Innovation, authored by Mark Purdy, managing director – economic research, and Paul Daugherty, chief technology and Innovation officer, Accenture.

The authors said AI may also be part of the solution to a US economy that is seeing a decrease in corporate profits growth, now at negative three per cent after a post-war peak of 25 per cent in 2010.

Accenture and Frontier Economics

The information and communication, manufacturing and financial services are the biggest winners in an artificially intelligent future. They will see a GVA increase by 2035 of 4.8 per cent, 4.4 per cent and 4.3 per cent, respectively, the report said.

That’s over $US 6 trillion in just those three sectors, according to Accenture’s research.

Source: Accenture and Frontier Economics

The good news is those who position themselves well now stand to grab a share of the profits, regardless of industry or country, with significant growth forecast in many developed countries.

“Artificial intelligence will revolutionise how businesses compete and grow, representing an entirely new factor of production that can ignite corporate profitability,” said Paul Daugherty, chief technology & innovation officer, Accenture.

It is “critical” that organisations move now, according to Daugherty, and develop and implement “strategies around AI that put people at the centre.” Businesses must maintain a people-first mentality and make bold and responsible decisions during AI integration, the authors said.

There are eight key strategies for leading organisations to consider in the process.

1.AI Strategy and Leadership

Enthusiasm for AI needs to come from the top, if it is to spread across the organisation. An AI roadmap endorsed by the C-suite will help create the cultural change necessary for full implementation, the report said. A good first step is for executives to have real interactions with AI technology.

“There is no substitute for visiting AI laboratories or innovation centres where experts can be probed, ideas can be tested and prototypes can be developed,” the report states.

2. Reinvent HR into HAIR

A lack of feelings notwithstanding, AI are still part of the workforce. They contribute value an interact like any other employee, the report said.

“The role of the Chief HR Officer will not only be about managing human employees, but also the supervision of AI workers—Human AI Resources.”

HR will need to develop and integrate with other departments, giving the CHRO a much bigger role in business strategy and innovation.

3. Learn with Machines

Just as AI is continually learning, human intelligence must continue to develop and interweave with machine intelligence, according to the report.

“With AI taking over mundane and low-value-added tasks, a skills gap will open up between young professionals and older workers, favouring those workers with experience,” the authors said.

Because of this, organisations must reconsider employee thinking and training. There will be “a  new emphasis on human abilities—judgment, communication, creative thinking—that complement technologies,” the report said.

4. Appoint a Chief Data Supply Chain Officer

Gartner predicts 90 per cent of large companies will have a chief data officer by 2019. But the role needs to be expanded or supplemented by a chief data supply chain officer, Accenture argues.

AI is only as good as the data driving it and data officers need to consider data as a supply chain in addition to data security and regulation, the authors said.

“A chief data supply chain officer will need to construct an integrated, end-to-end data supply chain, considering issues such as: What is the balance between internal and external data sources? What is the company’s data churn and cost per day? Where are the data silos? How can our company simplify data access?”

5. Create an Open AI Culture

It’s a big ask for employees to trust machines, particularly if they have the potential to impact their job. This is where an open AI culture can help.

“Humans and machines will be collaborating, teaching and learning from one another. This demands trust, openness and transparency, just as any co-working relationship,” the report said.

It’s up to leaders to be proactive in addressing the risks an opportunities that come with AI and a hybrid workforce, the authors said.

6. Step Beyond Automation

AI goes beyond automation and organisations that realise this can “harness the intelligence of dynamic, self-learning and self-governing machines,” the report said.

7. Take the Crowd into the Cloud

Open innovation models are being powered by crowds and the logical progression is to integrate this with cloud technologies, the report said.

“The next step in innovation will be to combine the crowd-sourced data in the cloud with AI capabilities to create new and disruptive business opportunities.”

8. Measure Your Return on Algorithms

Traditional metrics won’t cut it with AI. According to the report CFO will need to deploy a “new toolbox of financial metrics to properly asses the return on AI.”

One of the great attractions of AI and machine learning is their ability to appreciate in value over time.

“Unlike traditional assets that depreciate over time, AI assets, with their self-learning technologies, gain value as time passes. This compounding asset appreciation effect creates greater returns for companies that make early AI investments. In addition, although some of its applications have clear results, the learning nature of AI means that many of the bene ts will stem from yet-to-be determined sources,” the authors said.

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