This year has seen fast-growing interest in the emerging technologies of Artificial Intelligence (AI) and Machine Learning (ML) and their potential to dramatically transform how organisations think and act in the future.
But for many businesses, the value of the application of these technologies may not be obvious- therefore making it hard to justify making any sort of real investment. This is partly due to the fact many companies tend to underestimate how much data they have collected, and the value it might deliver.
Business analysts, from global firms such as Gartner and IDC are predicting that 2018 will see a sharp rise in the number of organisations who are deploying AI and ML technologies – as the opportunity costs of not acting will become more apparent for many businesses.
Gartner reported recently that 59 percent of organisations have started gathering information to build an AI strategy. By 2020 it estimates 30 percent of CIOs will have AI as one of their top 5 investment priorities.
AI has massive potential to enhance decision making, reinvent business models and ecosystems, and remake the customer experience.
However, because AI techniques are evolving so quickly, organisations will need to make smart investments in skills, processes and tools.
Businesses will need to identify some of the low-hanging-fruit on which to conduct small scale experiments to further build skills and confidence in this space.
AI is emerging as the next big battleground for the world’s most powerful tech giants. According to the 2016 McKinsey Global Institute, technology companies invested as much as $US39 billion in AI last year.
It also found that while 20 percent of firms that said they’re ‘aware’ of AI also said they were ‘adopters’, 41 percent of firms said they were ‘uncertain’ about the benefits of the technology.
Nevertheless, early evidence suggests that AI can deliver real value to serious adopters and can be a powerful force for disruption.
In a recent McKinsey’s survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the future.
The McKinsey’s survey looked at a number of specific examples across various market verticals including; retail, electric utilities, manufacturing, health care, and education, and concluded that AI will play an important role in improving forecasting and sourcing, optimising and automating operations, developing targeted marketing and pricing, as well as creating better user experiences.
But McKinsey cautioned there are no short-cuts for organisations heading off on their AI journeys, noting that the training of systems requires unique data sets, and can be challenging.
Nevertheless, those companies that are bold and make a start sooner rather than later will quickly find themselves at a distinct advantage early on.
“Companies cannot delay advancing their digital journeys, including AI,” said the report’s authors.
“Early adopters are already creating competitive advantages, and the gap with the laggards looks set to grow.”
A successful program requires businesses to address many elements of a digital and analytics transformation:
– identify the business case,
– set up the right data ecosystem,
– build or buy appropriate AI tools,
– and adapt workflow processes, capabilities, and culture.
In particular, McKinsey observed that leadership from the top, management and technical capabilities and seamless data access are key enablers.
AI promises benefits, but also poses serious challenges that cut across firms, developers, government, and workers.
Among the biggest challenges is how to reskill workforces, in order for organisations and workers to exploit AI, as opposed to competing with it.
Cities and countries serious about establishing themselves as a global hub for AI development will need to join the global competition to attract AI talent and investment.
Meanwhile, progress will need to be made on the ethical, legal and regulatory challenges that are almost certain to arise.
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