Digital Prospects - Personal Digital Recruitment & Head Hunting London

« Article List

 

Chief AI Officer: should every company have one?

Extract from the book "Technology vs People" available on Amazon

 

With so much discussion about the impact of new Ai technology, surely all companies now need to have a strategy, a plan about how to deal with it?

How manage these developing Ai and other new Tech innovations. Should the organisation be investing aggressively in this new Ai world or is that something better left to others, should we be in the vanguard or is it ok, at least for now to be a follower, are there rivals, competitors who might steal a march on us of we don't go for it, what will be the consequences if we do, what impact will it have on our workforce, on our people, on the morale and spirit of our organisation, what should we be doing, and what can we confidently ignore? Should we even pivot to become a software, information, knowledge house?

These are the sort of questions every business must consider, from the smallest to the biggest. The workforce will be looking to the leadership of the company to set out its stall, how safe are our jobs, can we use ChatGPT or CoPilot or whatever new Tech comes along or is that off-limits, something we can be aware of but should not be using perhaps for ethical or privacy or governance reasons? What is the plan?

In addition, external stakeholders, investors, analysts, partners, sponsors want an answer and they will be asking for both the short term and the long term for the next 3 to 5 years at least.

To do that, there's surely a need, indeed an imperative for a CAIO, a Chief AI Officer, some person with the knowledge, the understanding about the Tech and its range of possible impacts, who can be the point of contact to the Board and for all key stakeholders, who can be the champion of its benefits, and also the guardian against its possible damage, someone who can reassure that the AI and other new Tech opportunities and challenges are being very carefully considered and managed.

What's now changing the game is the sudden and recent leap-forward in machine intelligence.

Already today according to Gartner:

-45% of companies are now using AI widely across their business

-91% of companies are reviewing potential future investments

-85% of businesses have projects investigating how AI can improve customer services and reduce costs.

Spend on specified AI projects is expected to grow substantially, some research suggesting a quintupling over next 3 years (Gartner). Total AI "market size" estimated for 2025 at c. $140bn, likely to reach $1.5trillion annually by 2030 (IBM research). Research by IDC finds that biggest area of spend is "automation and improving efficiency". Other key goals include areas such as increased innovation, new product /services development, new ways to engage customers and speed up processes to get ideas to market more quickly.

In Financial Services, look for example at some of the leading retail banks like Barclays, Bank of America, Citibank and others. They are right now very actively exploring and utilising new Tech opportunities in their front and back office. Their plans include:

 

 

(i) branches replaced by online banking

(ii) telephone customer service representatives replaced by conversational bots

(iii) facial scanning required in the future for all ATM transactions (to be known as "smile to pay"!)

(iv) machine learning to enhance product cross-sell /upsell/ recommendation systems

(v) automation of threat intelligence and preventions systems

(vi) comprehensive fraud management via real-time monitoring of each and every potential customer interaction

(vii) fully automated claims processing

(viii) predictive IT operations maintenance

(ix) risk management: for example Santander's Corporate and Investment Banking division uses an AI-tool called Kairos that shows how a corporate client could be impacted by economic events, creating prediction patterns that enable employees to make more informed investment and lending decisions.

(x) research analysis: Bank of America has developed a platform called Glass that helps sales and trading employees uncover hidden market patterns to anticipate client needs. It does this by consolidating market data across asset classes with the bank's inhouse models and leveraging machine learning techniques.

Banks and Insurers are expected to be the biggest group of AI Tech investors. Pharmaceutical companies are hoping to especially benefit from more advanced and faster research capabilities to identify new drug compounds and treatments. General medical practice diagnosis and prescription could become a wholly automated set of processes (no longer a need to wait two weeks for a GP appointment?). In whatever sector we look at, whether front of house or back office or in manufacturing, or education or in Government, processes and people and focus of investment are all likely to be reviewed as AI Tech develops.

And does a company indeed have a choice? How does it weigh up its commitment to deliver increases in profitability and shareholder value, versus its commitment to people, to its employees, to manage staff motivation and morale, to deliver a balanced plan which isn't so skewed to shareholder advantage that it loses all sense of community and people responsibility?

So what would a Chief Ai Officer, a CIAO do? If a company is to make such an appointment, what should they expect this person to deliver? Is it just to accelerate a range of cost saving plans? Or is it something more fundamental, more advantageous, that could long term enhance the company's reputation, its place in society and the world, as well as bring value to its owners? And it does not have to be a high cost c-Level person, but it does need to be someone with stature and who will be listened to, someone that the Board can acknowledge as a true guide and leader and whose plans and strategies can be embraced, and implemented.

Let's look at some senior Ai chiefs in place today:

Philippe Rambach as the CAIO of Schneider Electric (global $30bn energy management/software). He was one of the earliest such senior appointments in the business world. His remit has been to establish a global AI hub and centre of excellence for the company.

Philippe discussed his appointment in this way:

"If you are a business owner who does not harness the power of the data available to you then you will have a tough time in the future economy.

In that respect we have no choice, we have to review how AI can help Schneider be a winner in the next 5 years so mastery of AI is vital.

We are using AI ever more widely. For example using IoT (internet of things) devices alongside AI can turn volumes of data into valuable energy insights so that we can track consumption trends and automatically finetune systems to ensure optimum efficiency.

Our key innovation hub in Grenoble is now a "smart building". It can interface with other buildings in the neighbourhood and could eg opt out in the event of a high demand for electricity to defer consumption, it's a smart grid-ready building and part of the energy landscape of tomorrow.

To achieve this, we have established a partner open eco-system, we cannot innovate alone, we are continuously developing our work with others through alliances, joint ventures and open AI solutions."

South Korea's Hyundai appointed a CAIO to its "Heavy Industries" division. Kim Young's role: to promote the application of AI and leverage of big data for Hyundai's shipping operations and ship construction. He has been especially looking at "developing AI-based autonomous navigation technology for unmanned vessels to allow ships to run on their own without a human crew and optimise navigation based on fuel efficiency." Hyundai have partnered with the global US data company Palantir Technologies and have already achieved a world-first by remotely and autonomously navigating a container ship across the Pacific.

Adrian Joseph became the first Chief Data and AI Officer at BT plc. He has encouraged the Board to adopt a simple but stark goal: "we will become an AI-led company.

Joseph was quick to announce the launch of AI Accelerator, a new platform and capability which will pioneer and oversee all AI developments made by the BT Data community. The aim "to determine business priorities for AI investment and ensure the targeted value-add and business gain is achieved. Also to substantially reduce software development time, from prototype to production targeting 6 days, down from 6 months and doing this by automated enforcing of templated best practices which the AI Accelerator platform will continuously develop."

Joseph has commented: "the platform will have built-in triggers to make sure that new AI use cases are properly assessed in line with guidelines on data privacy, security and ethics principles, ensuring the safe and responsible use of AI across the business".

All of which sounds encouraging though there's no explanation or elaboration on what those "ethics principles" in this context might be or what if any boundaries they represent.

One company that has made moves to establish that responsible AI is in fact Microsoft (sic) who have created the ("ORAI") Office of Responsible AI. It runs their Aether committee (AI, Ethics and Effects, in Engineering and Research). The ORAI has developed a set of core guidelines with the key message that: "Responsibility must be a key part of AI design, not an afterthought."

"At the start we received an exciting new model from Open AI called ChatGPT and straightaway we assembled a group of testers to probe the core model and understand both its capabilities and its limitations. The insights generated have helped Microsoft think about what are the planned mitigations and to bake in more safety features and controls. For example, we wanted to look at possible "hallucinations" where the model may make up facts which are not true. So we have designed ChatGPT so that it has responsible AI at its core".

Microsoft has now gone on to publish its Responsible AI guidelines aiming to establish it as an industry standard to "share its learnings and help our customers and partners navigate this new terrain. AI must develop as "technology built by humans for humans"

Such good and noble sentiments of course, but challenging to see the effectiveness of these guidelines and standards when we have an environment where ChatGPT had 100 million users within the first two months of launch and estimated to be more than 1 billion people worldwide in 2025, free to use or a subscription for just $20 and meantime being continually updated, new plugins, already new Versions launched and numerous start-up ventures exploring specific industry/user applications.

With all this, even more important for every company of any scale to have an AI champion. We might expect CAIOs to most typically come from a core Technology and /or Data

Analytics background, and for example Adrian Joseph of BT was a former Data & Analytics Partner at EY. Others like Di Mayze at WPP, Sanjeevan Bala at ITV, John Giannandrea at Apple share that technical expertise and know-how.

However what we have seen in some recent appointments is the need for people who know the company, have worked there for some time, know the people, have very good stakeholder skills and can build alignment and support for managing this new area.

So Philippe Rambach at Schneider comes from a Commercial /P&L management background without any previous Tech or Data expertise, but importantly he brings nearly 14 yrs working in various roles and different divisions across the company. He was well-known, respected and widely admired as a very good "key stakeholder manager". What Schneider realised was this role would need to be collaborative, would have to work across key functions, departments, SBUs to get alignment around Data and Analytics usage, investment, governance and controls and that was seen as their key to getting AI developed and progressing for the company.

The current holder of the Office of AI Responsibility at Microsoft is Natasha Crampton. Natasha is a lawyer by background, joined Microsoft in 2011 and became the Chief Counsel to their Aether Committee in "shaping, operationalizing, and advocating for Microsoft's policies on responsible AI."

Morgan Vawter in contrast is an academic, currently heading up AI and Data Science at Unilever, a background in consulting at Accenture, a former Adjunct Professor of Business Analytics at Columbia University, a Board member at the Chicago Technical Sciences Institute, a stint with Caterpillar before moving to the UK with Unilever, "a proven collaborator with world leading academic researchers across data science, technology, business, mathematics and psychology, a seasoned thought leader."

What we can see is that each and every company is at a different stage in their AI journey, that at any one time they need a different leader to navigate this challenging space for them:

-An academic to establish the capability and skills

-A commercial person who can translate ideas into new growth opportunities and revenues

-A process leader who can drive out efficiencies and performance improvement

-A collaborator who can build consensus around a strategy and roadmap plan

-A Governance /Risk Manager who can try to build in guidelines and rules and manage development.

What stage is your organisation at?

Whatever the challenges surely each and every Board and ExCo will need to review its current status and go about finding that champion, either an internal appointment or to hire and bring in the right expertise to help the company maintain its market progress, competitiveness and so build its future.

 

 

Excerpt also available for download as a PDF

 

 

 

© Michael de Kare-Silver 2024

Michael runs this specialist and international recruiting /headhunting practice Digital Prospects, helping companies recruit key talent where Digital Tech and /or Data skills and savvy are important.

Michael used to be MD at Argos.co.uk and of Experian.com, he is ex McKinsey strategy consulting and Procter & Gamble marketing, Michael provides a personal and dedicated advisory and recruitment service that delivers results and is built on treating people with kindness and respect.