AI beyond the buzzword

John Michaeledes at Slalom looks behind AI’s multi-industry takeover

 

AI is reaching deep into the workplace, with a recent survey showing that half (46%) of all knowledge workers use personal AI tools in their roles. For some, it’s because their IT team doesn’t offer AI tools, others said they wanted their own choice of tools, but for many, it’s because their company has banned external AI.

 

This isn’t uncommon. Just recently, law firm Hill Dickinson blocked general access to AI tools because “much of the usage was not in line with its AI policy”.

 

While clamping down on AI as an employer can trigger significant risks, including a breakdown in trust between employees, restricted productivity and falling behind industry competitors, it also raises questions around what an AI policy entails and who is responsible for its creation and delivery.

 

But before we assess the ‘who’, we have to establish ‘what’ AI is used for and ‘why’.

 

AI’s industry takeover

Industries are leveraging AI across a variety of functions, with implementation of AI in business typically falling into four distinct categories, each with its own considerations and impact.

 

The first category involves AI as a finishing tool for human endeavours. Businesses are increasingly using AI to assist in researching, drafting, refining, and proofreading communications and deliverables, which allows employees to focus on higher-value work.

 

Secondly, using AI to handle routine processes such as document processing or data analysis enables businesses to reduce human error, and free up valuable human resources. For example, in healthcare, AI is being used to collect and segment clinical trial data and patient records, which provides insights for personalised treatment plans.

 

The third category involves employee management applications. AI tools are being deployed to optimise workforce allocation, evaluate performance, monitor time and attendance, and match employees to projects based on skills and availability. These systems offer the promise of more objective, data-driven management decisions.

 

The fourth and perhaps most ambitious application is the creation of entirely new products or services powered by AI. Businesses are leveraging machine learning, natural language processing, and predictive analytics to develop innovative offerings that would be impossible without artificial intelligence capabilities.

 

The AI adoption checklist

Despite its transformative potential, successful AI implementation requires careful consideration of governance, ethics and practicalities. The question of who should be responsible for AI policy is paramount and varies based on the specific use case.

 

For AI used to assist in deliverable production, responsibility should lie with a cross-functional business strategy group. While the CTO or CIO has an important voice, technology leaders shouldn’t be the only decision-makers. As demonstrated by law firm Hill Dickinson’s approach, delivery, technology and data protection functions need to reach a unified position to balance competitive advantage with the protection of valuable intellectual property.

 

When AI is deployed to automate tasks involving personal information, policy should be co-owned by C-suite executives and the organisation’s Data Privacy Officer, alongside the cross-functional strategy team. Businesses must establish a legitimate basis for processing data with AI and implement safeguards against the weaknesses inherent in automated decision-making.

 

For workforce management applications, employee representation becomes crucial. AI policy in this domain should be consultative, with impacts transparently communicated to the workforce - this is crucial for maintaining workforce culture.

 

When developing new AI-powered products or services, the technical expertise of the CIO or CTO must be balanced with strong involvement from compliance and safety officers. This includes data protection officers and legal advisors who can ensure that AI products comply with industry regulations and broader legal frameworks.

 

Beyond governance considerations, businesses must justify their decision to use AI based on outcomes and uses rather than ‘doing it because everyone else is’.

 

The selection of appropriate tools is equally important. Organisations should conduct a thorough cost-benefit analysis that considers not just potential efficiencies but also new risks that AI tools introduce.

 

Cultivating an AI-ready culture

The introduction of AI tools requires careful consideration of how they will integrate with and potentially transform existing cultural dynamics.

 

Decision-makers can ensure their current leadership strategies meet both immediate and long-term organisational needs by aligning those with the organisation’s mission, vision, and values.

 

To do this, business leaders must adopt a flexible leadership style that balances immediate challenges with future uncertainties, while also developing skills and improving diversity outcomes.

 

Empowering employees and fostering a culture of innovation and accountability are crucial steps in this process. Additionally, promoting a culture of continuous learning and development helps keep the organisation agile and adaptable.

 

Again, just as businesses need to justify why they’re using AI, they should be communicating the ‘why’ to the workforce too.

 

Ensuring that teams have a clear understanding of the changes taking place, why they are happening, the positive impacts they deliver, and what they mean for the team is essential for successful implementation.

 

Looking ahead

It’s not as simple as implementing the most cutting-edge AI solutions but rather leveraging technology that aligns with specific business needs and integrating it in a sustainable and strategic way.

 

While businesses don’t want to miss the boat when it comes to AI, avoiding murky waters remains the universal challenge. The right balance must be struck - maintaining cultural integrity, upholding ethical standards and ensuring timely adoption of AI capabilities to remain competitive.

 

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John Michaeledes is Senior Principal at Slalom

 

Main image courtesy of iStockPhoto.com and ertigo3d