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The real value of AI for Australian organisations
There’s a huge amount of anticipation surrounding artificial intelligence (AI). But what does it offer your particular organisation?
AI offers opportunities for innovation and differentiation across all areas of business. However, while we’re likely to see wholesale business model transformation in some sectors, the focus in others will be more localised and iterative. Healthcare, automotive and financial services are the sectors set to receive the biggest boost to product value and demand from AI according to PwC’s AI Index.
Through our AI Impact Index, we also look at how improvements to personalisation/customisation, quality and functionality could boost value, choice and demand across nearly 300 use cases of AI, along with how quickly transformation and disruption are likely to take hold.
In this webcast, our expert panel will draw on PwC’s analysis of the business impact of AI to cut through the hype around AI to talk through valuable commercial openings in your market and how to take advantage of them.
AI Impact Index
Our sector specialists worked with market participants and our partners at Fraunhofer to identify and evaluate use cases across five criteria:
- Potential to enhance personalisation.
- Potential to enhance quality (utility value).
- Potential to enhance consistency.
- Potential to save time for consumers.
- Availability of data to make these gains possible.
Specific scoring parameters were derived for each criterion, and scores range from 1-5 (1 being lowest impact, 5 being highest). The parameters were weighted to arrive at a total Potential AI Consumption Impact. We also evaluated technological feasibility, and other drivers and inhibitors of consumer uptake. The results helped us to gauge time to adoption, potential barriers and how they can be overcome.
Explore the AI impact by sector
Personalization
Data Available
Utility
% Adoption Maturity
Near Term
(0-3 yr)
(0-3 yr)
Mid Term
(3-7 yr)
(3-7 yr)
Long Term
(7+ yr)
(7+ yr)
Time Saved
Potential AI Consumption Impact
Helping your business to make the most of AI
- Healthcare
- Financial services
- Technology, communications and entertainment
- Energy
Healthcare
Three areas with the biggest AI potential
- Supporting diagnosis in areas such as detecting small variations from the baseline in patients’ health data or comparison with similar patients.
- Early identification of potential pandemics and tracking incidence of the disease to help prevent and contain its spread.
- Imaging diagnostics (radiology, pathology).
Consumer benefits
Faster and more accurate diagnoses and more personalised treatment in the short and medium term, which would pave the way for longer term breakthroughs in areas such as intelligent implants. Ultimate benefits are improved health and lives saved.
Time saved
More effective prevention helps reduce the risk of illness and hospitalisation. In turn, faster detection and diagnosis would allow for earlier intervention.
Timing
- Ready to go: Medical insurance and smarter scheduling (e.g. appointments and operations).
- Medium-term potential: Data-driven diagnostics and virtual drug development.
- Longer-term potential: Robot doctors carrying out diagnosis and treatment.
Barriers to overcome
It would be necessary to address concerns over the privacy and protection of sensitive health data. The complexity of human biology and the need for further technological development also mean than some of the more advanced applications may take time to reach their potential and gain acceptance from patients, healthcare providers and regulators.
High potential use case: Data-based diagnostic support
AI-powered diagnostics use the patient’s unique history as a baseline against which small deviations flag a possible health condition in need of further investigation and treatment. AI is initially likely to be adopted as an aid, rather than replacement, for human physicians. It will augment physicians’ diagnoses, but in the process also provide valuable insights for the AI to learn continuously and improve. This continuous interaction between human physicians and the AI-powered diagnostics will enhance the accuracy of the systems and, over time, provide enough confidence for humans to delegate the task entirely to the AI system to operate autonomously.
Financial services
Three areas with the biggest AI potential
- Personalised financial planning.
- Fraud detection and anti-money laundering.
- Process automation – not just back office functions, but customer facing operations as well.
Consumer benefit
More customised and holistic (e.g. health, wealth and retirement) solutions, which make money work harder (e.g. channelling surplus funds into investment plans) and adapt as consumer needs change (e.g. change in income or new baby).
Timing
- Ready to go: Robo-advice, automated insurance underwriting and robotic process automation in areas such as finance and compliance.
- Medium-term potential: Optimised product design based on consumer sentiment and preferences.
- Longer-term potential: Moving from anticipating what will happen and when in areas such as an insurable loss (predictive analytics) to proactively shaping the outcome (prescriptive analytics) in areas such as reduced accident rates or improved consumer outcomes.
Time saved
The information customers need to fully understand financial position and plan for the future is at their fingertips and adapts to changing circumstances. Businesses can support this by developing customised solutions rather than expecting consumers to sift through multiple options to find the one that’s appropriate.
Barriers to overcome
Consumer trust and regulatory acceptance.
High potential use case: Personalised financial planning
While human financial advice is costly and time consuming, AI developments such as robo-advice have made it possible to develop customised investment solutions for mass market consumers in ways that would, until recently, only have been available to high net worth (HNW) clients. Finances are managed dynamically to match goals (e.g. saving for a mortgage) and optimise client’s available funds, as asset managers become augmented and, in some cases, replaced by AI. The technology and data is in place, though customer acceptance would still need to increase to realise the full potential.
Technology, communications and entertainment
Three areas with the biggest AI potential
- Media archiving and search – bringing together diffuse content for recommendation.
- Customised content creation (marketing, film, music, etc.).
- Personalised marketing and advertising.
Consumer benefit
Increasingly personalised content generation, recommendation and supply.
Timing
- Ready to go: Content recommendation for consumers.
- Medium-term potential: Automated telemarketing capable of holding a real conversation with the customer.
- Longer-term potential: Use-case specific and individualised AI-created content.
Time saved
Quicker and easier for consumers to choose what they want, reflecting their preferences and mood at the time.
Barriers to overcome
Cutting through the noise when there is so much data, much of it unstructured.
High potential use case: Media archiving and search
We already have personalised content recommendation within the entertainment sector. Yet there is now so much existing and newly generated (e.g. online video) content that it can be difficult to tag, recommend and monetise. AI offers more efficient options for classification and archiving of this huge vault of assets, paving the way for more precise targeting and increased revenue generation.
Energy
Three areas with the biggest AI potential
- Smart metering – real-time information on energy usage, helping to reduce bills.
- More efficient grid operation and storage.
- Predictive infrastructure maintenance.
Consumer benefit
More efficient and cost-effective supply and usage of energy.
Timing
- Ready to go: Smart metering.
- Medium-term potential: Optimised power management.
- Longer-term potential: More efficient and consistent renewable energy supply in areas such as improved prediction and optimisation of wind power.
Time saved
More secure supply and fewer outages.
Barriers to overcome
Technological development and high investment requirements in some of the more advanced areas.
High potential use case: Smart meters
Smart meters help customers tailor their energy consumption and reduce costs. Greater usage would also open up a massive source of data, which could pave the way for more customised tariffs and more efficient supply.
Work out what AI means for your business
The starting point for strategic evaluation is a scan of the technological developments and competitive pressures coming up within your sector, how quickly they will arrive, and how you will respond. You can then identify the operational pain points that automation and other AI techniques could address, what disruptive opportunities are opened up by the AI that’s available now, and what’s coming up on the horizon.
Prioritise your response
In determining your strategic response, key questions include how can different AI options help you to deliver your business goals and what is your appetite and readiness for change. Do you want to be an early adopter, fast follower or follower? Is your strategic objective for AI to transform your business or to disrupt your sector?
Make sure you have the right talent and culture, as well as technology
While investment in AI may seem expensive now, PwC subject matter specialists anticipate that the costs will decline over the next ten years as the software becomes more commoditised. Eventually, we’ll move towards a free (or ‘freemium’ model) for simple activities, and a premium model for business-differentiating services. While the enabling technology is likely to be increasingly commoditised, the supply of data and how it’s used are set to become the primary asset.
Build in appropriate governance and control
Trust and transparency are critical. In relation to autonomous vehicles, for example, AI requires people to trust their lives to a machine – that’s a huge leap of faith for both passengers and public policymakers. Anything that goes wrong, be it a malfunction or a crash, is headline news. And this reputational risk applies to all forms of AI, not just autonomous vehicles. Customer engagement robots have been known to acquire biases through training or even manipulation, for example.
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John Studley
Partner, Data Analytics and AI - Data Science capability, PwC Australia
Tel: +61 (3) 8603 3770
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