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- Tasks: Lead data strategy and AI initiatives to drive value in Agri-Food operations.
- Company: Join a large-cap Private Equity firm focused on innovation in the Agri-Food sector.
- Benefits: Competitive salary, dynamic work environment, and opportunities for impactful leadership.
- Other info: Fast-paced role with significant influence at board level and career growth potential.
- Why this job: Shape the future of Agri-Food with cutting-edge data and AI solutions.
- Qualifications: Proven executive experience in Data/AI and knowledge of the Agri-Food industry.
The predicted salary is between 150000 - 200000 ÂŁ per year.
A large-cap Private Equity sponsor is appointing a Chief Data & AI Officer (CDAO) into a scaled Agri-Food portfolio company to build enterprise-wide data foundations and industrialise AI as a core value-creation lever. The role will own the data strategy, AI roadmap, governance, and delivery of high-impact use cases across the end-to-end value chain—farm/inputs → production → quality → supply chain → commercial → finance—with clear linkage to EBITDA uplift, working-capital improvement, resilience, and improved decision-making cadence.
The CDAO will operate as a hands-on executive leader: shaping strategy, building capability, and delivering measurable outcomes at pace, consistent with PE timeframes and board-level expectations.
Key Objectives (First 3-6 Months)- Establish the Data & AI operating model
- Create a clear enterprise data vision and operating model (central vs federated), including ownership, stewardship, governance forums, and delivery cadence.
- Define the “single source of truth” for critical domains (e.g., product, customer, supplier, inventory, yield, quality, cost).
- Build the data foundations to scale AI
- Stabilise and modernise the data platform (cloud, lakehouse/warehouse, integration, master data, lineage, observability).
- Improve data quality, timeliness, and accessibility across core operational and commercial systems (ERP/MES/WMS/TMS/CRM, manufacturing/quality systems, IoT/plant systems where relevant).
- Deliver a prioritised AI value roadmap
- Identify and deliver a pipeline of AI/advanced analytics use cases tied to value creation, for example:
- Demand forecasting & S&OP optimisation (service levels, inventory reduction, waste reduction)
- Yield / throughput optimisation (process parameters, bottleneck management)
- Predictive maintenance (downtime reduction, asset reliability)
- Quality & food safety analytics / computer vision (defect detection, compliance)
- Procurement & commodity insights (pricing, hedging signals, supplier risk)
- Commercial analytics (pricing, promo, mix optimisation, trade spend)
- Traceability & compliance enablement (farm-to-fork visibility, audit readiness)
- Implement pragmatic, PE-friendly AI governance: model risk, bias testing, explainability, security, vendor risk, and regulatory compliance.
- Strategy & Value Creation
- Own the enterprise Data & AI strategy aligned to the sponsor’s value-creation plan and management priorities.
- Translate business goals into a quantified use-case roadmap with benefits cases, milestones, and owners.
- Establish KPI reporting tied to realised outcomes (not “activity metrics”).
- Data Platform & Architecture
- Lead the evolution of data architecture, integration, and data products across core systems.
- Ensure the data estate supports scalable analytics/AI (reliable pipelines, governance, standards, metadata, lineage).
- Drive simplification and interoperability across fragmented systems and spreadsheets.
- AI Delivery & MLOps
- Build repeatable delivery capability (product-based delivery, agile ways of working, MLOps, model monitoring).
- Partner with Technology/Engineering teams to deploy models into production, not just proof-of-concepts.
- Governance, Security & Compliance
- Establish data governance (policies, access controls, quality thresholds, master data).
- Implement AI governance (model approval, monitoring, auditability, vendor controls).
- Ensure alignment with relevant food sector expectations (quality, traceability, safety) and broader privacy/security requirements.
- Leadership & Culture
- Build and lead a high-performing Data & AI function (data engineering, analytics, data science, data product).
- Upskill business leaders and create a culture of data-driven execution—decision rights, dashboards, and performance routines.
- Stakeholder Management
- Influence at C-suite and Board level; communicate simply and commercially to senior stakeholders.
- Work closely with CFO, COO, CIO/CTO, Supply Chain, Manufacturing, Quality, Commercial, and Procurement leaders.
- Serve as a trusted partner to the PE sponsor/operating team (as required).
- Proven Data/AI executive leadership experience (CDAO/CDO/VP Data & AI or equivalent) delivering measurable outcomes, not just platforms.
- Experience in Private Equity-backed environments (compressed timelines, EBITDA focus, board cadence).
- Agri-Food domain knowledge: traceability, food safety/quality, seasonal variability, commodity dynamics, yield/waste drivers.
- Track record building data foundations in operationally complex environments: manufacturing, supply chain, logistics, FMCG/CPG, food production, or adjacent asset-heavy sectors.
- Demonstrable ability to create a prioritised AI use case portfolio, deliver at pace, and embed solutions operationally.
- Strong grasp of modern data stack principles (cloud data platforms, integration, governance, MDM, analytics engineering, MLOps).
- Excellent commercial storytelling—able to engage a PE board and translate technical delivery into value.
Chief Data & AI Officer in London employer: The Consultancy Group (London)
Contact Detail:
The Consultancy Group (London) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Chief Data & AI Officer in London
✨Tip Number 1
Network like a pro! Get out there and connect with industry folks on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can land you that CDAO role.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio of your past projects and successes in data and AI. We want to see how you've driven measurable outcomes before, so don’t hold back on the details!
✨Tip Number 3
Be ready for those tough questions! Brush up on your knowledge about data governance, AI ethics, and the Agri-Food sector. We need to demonstrate that we can handle the complexities of this role with confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Chief Data & AI Officer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in data strategy and AI, especially in the Agri-Food sector. We want to see how your skills align with our goals, so don’t hold back on showcasing relevant achievements!
Showcase Measurable Outcomes: When detailing your past roles, focus on the measurable outcomes you’ve achieved. Use specific metrics to demonstrate how your leadership in data and AI has driven value creation, particularly in environments similar to ours.
Be Clear and Concise: Keep your application clear and to the point. We appreciate straightforward communication, so avoid jargon and ensure your key points stand out. This will help us quickly grasp your fit for the role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at The Consultancy Group (London)
✨Know Your Data & AI Inside Out
Make sure you’re well-versed in the latest trends and technologies in data and AI, especially as they relate to the Agri-Food sector. Brush up on your knowledge of data governance, cloud platforms, and how to create a single source of truth. This will help you demonstrate your expertise and show that you can hit the ground running.
✨Prepare Real-World Use Cases
Think of specific examples where you've successfully implemented data strategies or AI solutions that led to measurable outcomes. Be ready to discuss how these experiences align with the company's goals, particularly around EBITDA uplift and operational efficiency. This will showcase your ability to translate technical skills into business value.
✨Understand the Business Landscape
Familiarise yourself with the company’s portfolio and the challenges faced in the Agri-Food industry. Knowing about traceability, food safety, and supply chain dynamics will allow you to speak confidently about how you can contribute to their objectives. It shows you’re not just a techie but also a strategic thinker.
✨Engage with Stakeholders
Be prepared to discuss how you would communicate complex data concepts to non-technical stakeholders, including C-suite executives. Practice simplifying your language and focusing on commercial storytelling. This will highlight your ability to influence and engage with senior leaders effectively.