Given the recent interest and proliferation of accessible generative AI tools, C-suite professionals must quickly educate themselves on the opportunities this technology offers.
A global survey of the C-suite by Accenture found that 94% of leaders anticipate spending more on technology in 2024, with 75% specifically mentioning AI and machine learning (ML) as key areas of investment.
A basic understanding for all leaders
“We’re past the question of ‘if’ AI should be integrated into their business strategies,” says Christopher Lane, head of data and AI, Accenture UKI. “It’s more a question of: ‘How do I confidently harness AI for efficiency and growth while the road is still being built and the guardrails are not yet in place?’”
This lack of a roadmap is causing concern for leaders. “The more we apply AI, the more we see its potential to augment human performance in ways that just 18 months ago would have been unimaginable,” says Lane. “There is a fundamental concern we’re hearing about whether organisations can keep pace with the technology.”
So, what knowledge do leaders need to feel more confident and secure as they progress themselves and their companies during this uncertain but exciting time?
While leaders may not need to learn the deep intricacies of an algorithm, they do need to have some understanding of how generative AI works. This is particularly true for CEOs, as they balance challenges and opportunities stewarding their companies. However, they will need support from the technical leadership within the organisation.
“Generative AI is progressing extremely quickly with significant upside, but also risk which needs to be managed,” Lane explains. “Decisions taken now could impact strategic positioning in the future so an understanding of some of the mechanics of the technology, how it works and how it is deployed is essential.
New responsibilities for technical leaders
“This is not all on the CEO,” says Lane. “It is critical they have a C-suite around them that is AI literate and contains individuals with a real depth of competence and understanding. For years we’ve championed the need for deep technical proficiency in the C-suite. In line with this, we believe the chief technology officer (CTO), chief information officer (CIO) or chief data officer (CDO) will continue to play a decisive role in providing the technical insight and assurance for key decisions.”
Those leaders with remit over technology and data will need to keep fully abreast of the latest developments in the space, informing their peers and providing insight on the value of new investments.
“Tech and business strategies will become increasingly intertwined, so the decisions that CTOs make have a determining effect on the future of the business,” says Lane.
To fulfil this role, CTOs, CIOs and chief information security officers (CISOs) must develop both their own and their team’s data management capabilities, while also leading on migrating their company to the cloud, if they haven’t already.
“To unlock the fundamental value of data and AI, businesses need a solid data foundation centred on a thoughtful data migration strategy, a modern enterprise data platform on cloud, and a trusted, democratised and reusable set of data products that improve efficiency and speed to uncover new and actionable insights,” says Lane.
Developments for non-technical leaders
These evolutions will, of course, need new skills to be acquired in the business. Chief human resources officers (CHROs) or chief people officers (CPOs) will have crucial roles to play in talent acquisition and reskilling the existing workforce.
“Our analysis suggests that up to 40% of all working hours across industries could be impacted by generative AI,” Lane explains. “In this context, the essence of the CPO role may remain the same, but the scale and pace at which the workforce will need to evolve will be unprecedented and the criticality of the role amplified.”
The scale and pace at which the workforce will need to evolve will be unprecedented
Lane says that CPOs must fulfil two key roles in this new paradigm. Identifying and acquiring the skills needed to develop new AI-powered applications and creating a continuous learning culture that helps all employees work alongside generative AI.
One area of the business that may have a headstart in this endeavour is the marketing team. Data from Econsultancy shows that 75% of marketers are planning on or are already using generative AI. Therefore, chief marketing officers (CMOs) must understand the possibilities in content production and how much money they can potentially save.
While CMOs will be glad of the ability to stretch their budgets, there are significant legal and ethical questions which must be considered. They will need to stay up-to-date on the latest developments in copyright law, as the battle for who owns the intellectual property of AI-generated content rattles on. Lane also points out the potential negative backlash against AI-generated creative.
“I know many creatives are terrified that the temptation to save money through delegating to technology will outweigh the benefits of human-created assets that may be more likely to delight their customers. This poses a fascinating question for CMOs around what modern creative excellence looks like for their organisations.”
A collective challenge
Collectively, the C-suite must work together to deliver value on their technological investment. Lane suggests that this comes from identifying the processes that can be improved by generative AI, before testing the company’s ability to adapt to those changes.
The chief financial officer (CFO) will be crucial here. They will be best placed to contextualise the value of adopting new technologies and prioritise different strategic needs across the business. Machine learning programmes will likely bring efficiency here, as access to business insight reports should allow financial leaders to easily spot opportunities and risks.
Addressing those potential stumbling blocks will again be a concern for the entire executive team. Accenture’s data shows that while 69% of businesses have started implementing responsible AI practices, only 6% have operationalised that capability from end to end.
“The desire to capitalise on AI innovation should never come at the expense of algorithmic transparency, privacy and data security,” says Lane. “This cannot just be about frameworks and principles, it needs to be backed up with systemic monitoring of how they are being applied.”
