The Role of AI in Transforming Business Headquarters

Artificial Intelligence (AI), and particularly Generative AI (GenAI), have significant potential to drive efficiencies in businesses – however, it is often not being utilised to its fullest potential. Most companies have a long list of use cases for AI – some of which have been successfully installed – but this is not a comprehensive AI strategy. To see the full benefits of AI tools, businesses must adopt a structured, forward-thinking approach to implementation and long-term use.

AI Use Cases

Use cases for AI currently almost solely focus on enhancing efficiency. Our study of over 200 applications revealed that most improvements were incremental, offering measurable time and resource savings, with only 20% of use cases impacting business models.

Incremental efficiency gains, such as AI fact-based negotiations, identification of invoice errors or creating marketing content, offers measurable time and resource savings. Business growth driving use cases include online offers, customer targeting and product offer and own brand improvements as well as reduced product development cycles.

AI driven business transformation (especially if focused on efficiency gain or cost improvements only) must not target a single use case implementation. It requires a more holistic picture:

• If efficiency is the goal of AI adoption, businesses should consider how an AI-digital headquarter could look, and if this can be used to reduce operating costs.
• If business growth is the goal, businesses should consider how an AI-digital G2M strategy could look – including shortened product development, and improve product offering, and how consumer data can be used to improve sales channel life cycles.

Efficiency Potential Across Departments

The potential for AI impact varies across departments, with some functions being more suited for automation than others. We found the highest potential for AI in Marketing, IT, Category Management & Procurement, and E-Commerce:

• Marketing: Content creation and campaign optimisation are ripe for automation. AI can draft press releases, personalise ad strategies, and manage digital campaigns.
• IT: From coding support to cybersecurity enhancements, IT departments benefit from AI’s ability to process large datasets and automate complex workflows.
• Category Management & Procurement: AI can support with contract analysis, identifying cost-saving opportunities, and ensures better supplier negotiations.
• E-Commerce: Automating customer service interactions and optimising product listings enhance the customer journey and operational efficiency.
  Departments like HR and finance also benefit, though their tasks (e.g., payroll, compliance) tend to adopt AI more slowly due to complexity and sensitivity.

Impact of AI on Business Skills Mix Requirements

The integration of AI into headquarters will require new skills and roles to bridge business needs with technical solutions. Key roles will include:

• AI Process Expert: Aligns AI capabilities with business goals and ensures seamless integration.
• AI Scientist: Specialises in building and fine-tuning AI models and algorithms.
• AI Consultant: Identifies opportunities, quantifies benefits, and prioritises AI implementation strategies.

A key question for businesses is where these new roles will sit – within centralised IT teams, or within the business unit they will support? Both have benefits and drawbacks. Centralising functions within IT teams can support resource sharing, and ensure governance and ethical standards are met, but may create distance with other functions.

Placing AI roles within business functions can close feedback loops during AI development, help identify and overcome challenges quickly, develop better understandings of individual departments needs of AI, and support agile working, but can create challenges in resource sharing and uniform adoption.

Businesses must strategically balance these roles to maximise the potential of AI while addressing workforce transformation challenges.

A Structured Approach to Identifying AI Potential

To unlock AI’s benefits, businesses need a clear roadmap. A structured, four-step framework is essential:

Define the Target Picture (beyond just use cases)

• Set the efficient target picture (top down)
• Align the organization behind it

Activity Prioritisation:

• Record and classify tasks across headquarters functions.
• Estimate AI’s impact based on productivity gains and implementation ease.

Gap Analysis:

• Assess existing solutions and identify skill gaps.
• Evaluate whether to build custom solutions or adopt external tools.

Governance Framework:

• Document current organisational structures and define a future AI-enabled setup.
• Establish ethical standards, resource allocation, and accountability.

The potential impact of AI is one of the most hyped topics across industries – but firms still struggle to get traction in leveraging the full potential of AI. To move beyond incremental efficiency gains, companies must adopt a holistic approach to prioritise applications, develop the right skills mix and adopt a structured approach to adoption.

Read our full report below – or reach out to our experts for more insight into AI adoption.