AI strategy: playbook insights from PwC and Infosys

Anand Rao is Global Artificial Intelligence Lead at PwC
Anand Rao is Global Artificial Intelligence Lead at PwC
Artificial Intelligence specialists from PwC and Infosys share their AI Strategy Playbook advice for global business leaders to leverage tech opportunity

Artificial Intelligence promises a genuine opportunity for your organisation, but do you know how best to implement this technology to make the most of the transformational possibilities? Probably not. Which is why Business Chief has turned to two leading voices in AI to provide a Playbook for AI Strategy. 

Anand Rao is Global Artificial Intelligence Lead at PwC, and the leader of the Big 4 consultancy’s AI and Emerging Technology practice. With more than 35 years of industry and consulting experience, he leads a team of practitioners who advise C-level executives and implement advanced analytics and AI-based solutions on a variety of strategic, operational, and ethical use cases. 

Alec Boere is Associate Partner for AI & Automation, Europe at Infosys Consulting. A seasoned disruptive design and technology expert with over 20 years of experience within the technology space, Alec advises brands and corporations on the strategic development and delivery of cost saving, revenue generating or category differentiating disruptive technology products and services.

Business Chief: Why is AI significant for the future of business?

Anand Rao: AI is impacting every industry sector and every functional area. It is a general purpose technology that will have a profound influence in the next 10-20 years on how we interact with each other and how individuals, businesses, and governments make decisions. AI will automate a number of repetitive and manual tasks while also assisting and augmenting human decision making. 

In some cases they are also moving from automating and transforming today's businesses to disrupting our current business models. We are already seeing fundamental ways in which AI has changed our behaviours – from searching for content, to summarising and synthesising what we read, see, or hear, to even creating new forms of art, music, and literature. As a result, businesses that ignore AI are doing so at their own peril.

Alec Boere: From the personal assistants in our mobile phones, to the profiling, customisation, and cyber protection that lie behind more and more of our commercial interactions, AI touches almost every aspect of our lives. And it’s only just getting started.

Value can be had across the organisation, in terms of productivity, personalisation, time saved, and quality.

For example, with the enablement of a truly personalised experience (whether B2C, B2B or E2E). AI can deride the gaps that you might have in terms of data volume (traditional methods couldn’t) to drive out customer vectors. 

More recently we are also seeing an increase to the promised labour productivity gains, whereas AI can help co-pilot decision making to increase the effectiveness of resources in the Enterprise. This also has effects on time saved and the quality of the outputs. As an example we have been using synthetic data to help organisations to better predict outcomes that balance the decisions needed around product/ service quality.

There are also softer benefits which are more difficult to determine an ROI from the application of AI such as the improvement of working practices in the enterprise for staff which helps with talent retention but also that of the agility of the organisation.

BC: Do you feel CEOs understand the potential of AI?

AR: I don't think CEOs fully grasp the potential of AI. Many can understand the potential impact that AI can have on the economy (eg. US$15.7 trillion by 2030 - see Sizing the Prize report). However, most CEOs are unable to grasp the implications for their own business. Every industry sector and business needs to transform itself by using data, analytics, automation and AI. CEOs should consider this as part of the continuing evolution of digital transformation. Setting up a Centre of Excellence, designating clear ownership, and recruiting the right senior management are critical CEO functions to ensure that their company is not left behind in the AI race. 

AB: Yes and no, CEOs are constantly being reminded of the value AI can deliver but not all are benefiting. There is still a big gap between the leaders and the followers, as you would expect. Whilst this is closing, there is still a lot of resistance within mid-management levels within the enterprise. 

BC: Is the C-Suite resistant to the adoption of AI?

AR: I don't think the C-Suite is necessarily resistant to the adoption of AI as much as they do not appreciate the importance of AI in transforming the organisation. Even if they appreciate the importance of AI they are not fully aware or equipped to handle the challenges associated with designing, building, and deploying AI across the enterprise. Organisations that were early adopters of digitisation are better equipped to expand their digital transformation initiatives into automation and AI initiatives. They are better able to capitalise on the move to cloud and the resulting use of AI/ML on the cloud to centralise the data and gain better cost efficiencies and decision effectiveness. 

AB: No, it is the balance of the change that AI will bring. Over the last few years we have completed 100s of POCs but in the last 18 months there have been better ways to manage the challenges of getting the benefits from AI. The main challenges are that of ROI (how to measure), deployment (going beyond the POC) and that of trust and ethics. 

Making sure you have these three core elements managed will ensure better success and bottom-line success in the adoption of AI across the Enterprise. 

BC: With a talent shortage and skills gaps, can AI help solve these issues?

AR: AI is being used by HR departments to both source talent and also match individuals with the right skills to the right jobs. However, one should make sure that we are not perpetuating institutional bias when recruiting or monitoring the performance of staff. Adopting responsible AI practices can alleviate some of these concerns. AI, especially in the form of contextual learning, can help train staff better and faster in standardised settings like call centres or service centres. AI can also augment the decision making of humans and learn from the experts to raise the general level of proficiency of all staff.

AB: Yes, certainly. But, it needs new thinking to challenge the status quo down to every business process and functions. Where AI is truly scaled across the organisation there are huge benefits that can be gained. 

On a more practical note, for example within HR functions, we are using AI to predict staffing needs, unpacking unknown skills (latent skills) in the enterprise but also, most importantly, helping determine the right learning gain or learning path for the enterprise’s existing talent pool so they can meet the changing needs of the organisation. 

In addition with the increase of the adoption of low code platforms this is helping IT departments democratise a once siloed capability to give business owners the tools to constantly improve their end service – whether from a process optimisation or driving a better customer experience.

BC: How will the human workforce benefit from AI adoption?

AR: AI can help the human workforce by enabling the 3 As – Automation, Assistance, and Augmentation. Routine jobs can be automated by AI, relieving users of dull and boring jobs. However, one needs to ensure that these routine jobs that are done by humans have other alternative jobs to pursue. Failing to do so will cause significant social disruption. 

AI can also assist humans in doing their jobs better. A number of jobs in the services sector today are assisted by AI that can crunch through large volumes of data and make inferences faster than humans. Finally, AI can also learn from how humans are doing their jobs, find patterns, enhance the way we make decisions, and lift the overall effectiveness of human decision-making. Today, AI is working side-by-side with human artists, movie producers, script writers, journalists and other creative artists to generate and enhance creative content.

AB: Though co-piloting, AI will help the workforce become more productive and ultimately more satisfied that they are completing their tasks more effectively. But, in order to enable this, organisations that want to scale AI in the enterprise need to do so with the right controls, ensuring the use of AI is ethically-aligned and a decision-award culture is adhered to.

BC: What advice would you give a business leader looking to take their first steps in AI?

AR: Business leaders wanting to adopt AI should have three maxims in mind. 

1. Think big, but start small. AI leaders should have a good understanding and develop a vision of how to embed AI across the entire enterprise, but must start with a single business or functional unit to demonstrate the value of AI and build the right skills. 

2. Build a proof-of-concept, scale, and maintain. AI leaders must start building proof-of-concepts to ensure that the AI can have the desired performance from the systems before they start scaling the application across the enterprise. After the AI system has gone into production, organisations need to constantly monitor the performance of the AI system to ensure that it is adapting to the changes in the environment. 

3. Adopt a portfolio approach to ROI. AI leaders should have a portfolio of AI initiatives with the right mix of complexity of models (e.g., simple models that have already been built by other groups within the organisation or by competitors to more complex first of a kind models in the industry). Some of the AI initiatives may fail to deliver the appropriate performance and should not be deployed in production, while a few may exceed the benefit expectations. The objective of the AI leader will be to deliver the overall portfolio ROI as opposed to necessarily delivering an ROI on every AI initiative.

AB: First steps should be to determine your measurement approach (so you can better determine the ROI), ensure you have a clearly defined deployment approach (getting beyond POCs) and most importantly have a clear approach to the change (ethic and trust, challenges that you will encounter). These are the basis of your operating model, from which you can then prioritise the use cases across the enterprise.

BC: How do you see AI developing in the next three years – how will it impact business and society?

AR: Three key AI trends are worth watching out for in the next 3 years:

1. Deployment of AI models – more organisations will move from experimenting with AI to fully deploying AI models, often along with other software applications in the cloud. This will significantly enhance the customer experience as well as improve staff productivity and effectiveness. 

2. Democratisation of AI – several AI applications will be standardized and simplified enabling the democratisation of AI. This will allow staff without the necessary expertise in AI to operate and manage AI solutions. 

3. Responsible AI – as more AI models get deployed and used by a larger proportion of non-expert users companies will focus more on Responsible AI to ensure that the AI acts in an ethical manner 

AB: AI will become more pervasive within the enterprise. A day when AI is truly at scale through its injection of AI across business processes whether in Auto-pilot of Co-pilot.

The impact will be that we will have different tasks for the workforce. But we will certainly be more productive and effective in the use of resources to deliver products and services.

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