How the UK's Invest 2035 Strategy Empowers Data Professionals and Business Leaders

Eden Smith • June 25, 2025

With the UK’s   “Invest 2035” modern industrial strategy now live, business leaders and data professionals face both a unique challenge and opportunity. This 10‑year blueprint, reinforced by £22 bn+ in R&D funding and deep energy policy reforms, puts digital transformation, AI, and data-enabled innovation at the centre of national productivity.


For business and data professionals alike, this is a wake-up call to align, adapt, and lead.

In this article we wanted to explore how our community, as data professionals and as business leaders, can respond to elevate their professional careers and lead in business.


Guidance for Data Professionals at Every Stage


Entry-Level (Career Starters)

e.g. recent grads, bootcamp completers, apprentices


Key Advice:

  • Build foundational skills fast: Focus on SQL, Python, Excel, data visualization (Power BI/Tableau), and cloud basics (Azure, AWS).
  • Work on real projects: Freelance, open-source, or personal projects build credibility.
  • Apply even if you’re not 'ready': Hiring is now based more on potential and portfolio.
  • Use new routes: Look at apprenticeships, graduate schemes, NHS Digital, ONS, GDS.
  • Understand your chosen sector: Data needs vary across retail, charities, health, energy.


Junior Professionals (1–3 Years Experience)

e.g. data analysts, junior data scientists/engineers


Key Advice:

  • Sharpen your niche: Decide your path: engineering, ML, BI, or AI ethics.
  • Ask for stretch projects: Innovation sprints, cross-functional teams offer growth.
  • Improve communication: Learn to present your insights clearly.
  • Build your public portfolio: GitHub, blogs & LinkedIn profiles matter.
  • Upskill smartly: Cloud data platforms (e.g. Databricks), domain skills, or AI tools.


Mid-Level Professionals (3–7 Years Experience)

e.g. analytics leads, senior engineers, data scientists


Key Advice:

  • Solve business problems, not just technical ones. Be proactive.
  • Mentor others: Develop leadership and communication – our Nurture Programme is great for adding capability to your team and demonstrating your skills in leadership.
  • Bridge technical and commercial teams. Find ambassadors, solve challenges and win hearts and minds.
  • Build professional networks: Meet people in person and be active in webinars – try Big Data LDN, Women in Data, AI for the Rest of Us, The OR Society.
  • Think like an architect: Scalable systems, governance, model ops.


Senior Data Leaders (8+ Years / Heads of Data, CDOs, etc.)


Key Advice:

  • Use Invest 2035 as a strategic lever: Justify data investments by tying them to productivity and sector growth.
  • Champion ethics & diversity: Stay ahead of privacy, ESG and governance trends.
  • Upskill and reskill internally: Create academies, support apprenticeships and build talent pipelines and succession plans that support diverse teams and cross-skilling.
  • Build influence externally: Speak, publish, sit on boards.
london city scape

What Business Leaders Should Do Now


1. Align Data Strategy with National Priorities
  • Put data at the centre of business strategy: Tie data initiatives to revenue, cost, satisfaction, compliance.
  • Map your data goals to IS‑8 sectors: e.g. predictive maintenance in manufacturing, demand forecasting in energy, creative analytics in media.
  • Frame case studies using industrial strategy language: cost-savings via efficient grid use or exporting AI solutions within clean energy.


2. Invest in Talent to Fuel Innovation
  • Invest in the right roles: Build cross-functional data teams that span ops, product, finance.
  • Create a data-literate culture: Build internal confidence and reduce reliance on specialists. Where using consultancies, make sure you look for a team with a focus on people, knowledge transfer and an exit plan.
  • Recruit for skills and leverage global talent using brighter visa paths.


3. Leverage Regulatory & Financial Tailwinds
  • Exploit energy cost savings from subsidy schemes: reallocate those resources into data infrastructure.
  • Use public procurement reforms to bid for government-backed digital pilots and innovation tenders.


4. Use Regional Clusters & Collaborations
  • Use public-private opportunities: Tap into Innovate UK grants, AI accelerators, and regional data clusters.
  • Build partnerships within regional industrial clusters (e.g., West Yorkshire, Midlands, Scotland).
  • Engage with local councils and devolved bodies to co-design data-driven initiatives aligned with regional growth strategies.


5. Be Data-Aware in Governance & Ethics
  • Establish trust through governance: Compliant, clean, ethical data is a reputational asset and essential for carbon reporting.
  • With heavy R&D and AI focus, establish robust data governance, privacy, and responsible AI frameworks.
  • Engage with the new Industrial Strategy Council and be ready for annual progress monitoring and compliance metrics


6. Create Value Through Metrics & Storytelling
  • Define and track value: Set clear KPIs: time saved, insights delivered, churn reduced and tie to the strategy’s objectives: energy saved, processes optimised, new revenue streams in priority sectors.
  • Frame achievements in narrative form: "X% CO₂ reduction in our clean energy operations", or "AI-driven supply chain cost savings".


In summary


Invest 2035 is more than an economic plan. Professionals must prepare, and leaders must guide - because data maturity will define market leadership in the years ahead.


Business leaders must embed data at the core of innovation, finance, and operational decision-making to ride the Invest 2035 wave.


Data professionals should seize new talent pipelines, grand-challenge funding, and cross-sector collaborations to show measurable impact. Together, this alignment will bolster competitiveness - not just for individual firms, but for the UK as a data-powered, industrially resurgent nation.

By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
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