AI spending increased by a massive 62% last year and this trend shows no signs of abating.
Substantial investments in AI often come off the back of successful digital transformations and data management projects, and organisations that have seen success are 81% more likely to have advanced data management capabilities and are 73% more likely to have mature cloud capabilities. In this way, we can see that the ability to capitalise on AI is directly related to an organisation's willingness to take a leadership approach to technology and perceived to be an opportunity for significant competitive advantage.
The use cases for AI are varied -- one report shows that 57% of organisations are using AI to help improve or develop products, while a further 54% are using AI to help optimise systems and reduce business costs. In healthcare, it's seen as an opportunity for cost savings (50%), particularly in regards to administration, where 62% of healthcare organisations trust the use of AI for those tasks.
Meanwhile, both marketing and risk executives have embraced AI as a competitive differentiator (66%) even though many struggle to adequately clean and prepare data for analysis. Educating employees on how to adapt to work with AI-driven systems will be key to successful adoption in the future and 87% of healthcare leaders believe that hiring new employees that have experience in working with AI is a priority.
In short, AI presents opportunities for organisations to find new efficiencies through the automation of a great number of processes. With businesses being highly disrupted and employees isolated from their teams as a result of COVID-19, being able to draw on AI to automate essential processes is a pathway that will help organisations maintain productivity and improve customer experience.
AI in action
Making road travel safer: The Road Safety Commission of Western Australia turned to AI to grapple with the difficult challenge of maintaining road safety in Australia's largest state. One of the most useful tools that the Road Safety Commission of Western Australia utilises to limit accidents is its red-light speed cameras. However, manually determining where to place them based on statistical analysis is time and labour intensive and not always accurate in determining where the greatest risks actually are. By partnering with SAS, the Road Safety Commission of Western Australia was able to improve its accuracy and efficiency in determining where the greatest risks were on the roads while also maximising the value of its deployed red-light speed cameras.
Read more about how the Commission leveraged AI to save lives.
Helping citizens return to work: Over in NSW, Insurance and Care NSW (icare) had been using a "one size fits all" claims process for 30 years. Its system, however, began to show its age, both in terms of the services provided and its ability to help workers transition back into the workforce after injury with the appropriate level of care.
For icare, the challenge boiled down to this: Two people with the same injury may not need the same level or type of support, and manual systems are notoriously inefficient at understanding this degree of nuance. After partnering with SAS, icare was able to deliver an increase in accuracy of service by 15% and could now call on over a year's worth of de-identified claims data in an instant. This increase of accuracy to its models also came with the ability to process claims in near real time.
Read more about the icare experience with AI.
SAS's ability to deploy leading data analytics and AI solutions to help organisations deliver efficiencies and better accuracy has been recognised by Gartner, which placed SAS as a "Leader" in its Magic Quadrant for data science and machine learning for seven consecutive years. Maintaining that leadership position is not easy, because as Gartner notes, it's a space that goes through continual disruption: "As with last year's Magic Quadrant, vendors are heavily focused on innovation and differentiation, rather than pure execution. Innovation remains key to survival and relevance."
Taking steps into AI
To help organisations make inroads into their AI journey, SAS has produced an e-book titled How To Take AI Projects From Start To Win. One of the challenges that organisations face with AI is building strategy around it. As one report notes, while 93% of executives expect to get some value from AI, 65% reported that they have yet to see value from their recent AI investments.
Investment in technology itself is only part of a successful AI deployment. SAS notes in the e-book that there are four pillars for success in any AI project: In addition to technology investment, an organisation needs to develop clearly defined goals and objectives up front, build new processes around the technology, and ensure that the organisation's people are all motivated behind the solution.
"The perception that you can push a magic button and get the answers that you need is misleading," SAS said. "It's a much better approach to lay a solid foundation that takes you from start to finish and allows you to build and mature your AI initiatives based on what you've learned along the way."
The success of Road Safety Commission of Western Australia and icare, as noted above, comes down to their understanding that the successful implementation of AI hinges on these four pillars. In engaging with SAS, both organisations were able to pair technology with vision, while also crafting compelling AI solutions that have benefitted both the internal staff in doing their jobs, as well as their customers -- in this case, the broader Australian community.
Begin developing your strategy around AI and data by accessing this e-book from SAS.