Dr David Bozward

Tag: sustainability

  • What UK businesses can learn from Ukraine’s innovation ecosystem

    What UK businesses can learn from Ukraine’s innovation ecosystem

    Ukraine’s innovation ecosystem offers UK businesses a practical lesson in turning expertise into useful products quickly. Its experience brings the relationships between entrepreneurs, government, universities, investors and customers into sharp focus. Russia’s invasion has imposed devastating human and economic costs. Within that reality, Ukrainian organisations have developed approaches to collaboration and delivery that deserve careful examination by British business leaders.

    These capabilities have deep roots. Ukraine has an established base of software engineering and technical expertise. A July 2026 EU4Innovation East assessment estimates around 2,600 active startups, while highlighting weaknesses in finance and commercialisation. The ecosystem combines private enterprise with public platforms, research institutions and international support. Its successes provide examples to learn from, alongside substantial unfinished work. EU4Innovation East

    One example is Diia, Ukraine’s digital public services ecosystem. It brings official documents and government services into an app and online portal, including registration for sole traders within minutes. This demonstrates how administrative design can support entrepreneurship. For a UK business, the equivalent opportunity might be simplifying customer onboarding, supplier registration or access to internal expertise. information about the project Diia

    Start by following a routine transaction through the organisation. Count the forms, approvals, repeated requests and waiting days. Then give someone responsibility for removing unnecessary steps. Buying software alone rarely resolves a process whose underlying design remains cumbersome. Innovation becomes more accessible when staff and customers can act without navigating avoidable obstacles.

    Ukraine’s BRAVE1 defence innovation cluster illustrates another approach. It connects developers with military users, investors and government, combining financial support with testing, feedback and help spreading technologies into use. In September 2026, BRAVE1 reported that developers had received more than 1,000 grants since 2023. My reading of this model is that money becomes more useful when accompanied by access to users and practical validation. brave1.gov.ua

    British firms can apply that principle in civilian settings. A small UK manufacturer could invite a small technology company to tackle a specific maintenance problem, provide access to operators and fund a limited trial. Both parties would agree the performance measures before starting. A successful experiment should have a named buyer and a realistic route into routine operations.

    The same method could strengthen business resilience. A food producer might test alternative suppliers or energy arrangements before disruption occurs. A professional services firm could rehearse recovery from a cyber incident with its technology provider. In each case, a short exercise would expose assumptions about people, systems and dependencies. This makes innovation relevant to continuity and leadership, alongside product development. Managers would learn whether a proposed improvement works under pressure, and which resources must be available for it to deliver the intended benefit.

    Universities also have a role beyond supplying research. The European Commission describes Ukraine’s developing network of university and research institution startup schools, incubators and accelerators. These initiatives bring entrepreneurial training, mentoring and prototyping support together. Their development reflects a challenge shared by many innovation systems: helping people convert technical knowledge into products that someone can use and purchase. Research and innovation

    UK businesses already have a mechanism for deeper academic collaboration through Knowledge Transfer Partnerships. These partnerships connect a business with academic expertise and a qualified graduate working on an identified innovation challenge. For employers, the opportunity extends to developing staff capabilities. Students and graduates gain practical experience, while the business builds knowledge it can continue using after the project. UKRI

    Finance needs to support the transition towards adoption. In December 2025, the European Innovation Council described a €20 million scheme supporting Ukrainian technology businesses as they advance from laboratory validation towards demonstration. The broader lesson for UK leaders is to allocate resources across successive stages of development, including testing and implementation. An impressive prototype still needs investment before it can become a dependable commercial offering. European Innovation Council

    Large businesses can help by becoming early customers. A modest paid pilot can provide a startup with revenue, evidence and a reference customer. Procurement teams should establish proportionate requirements and agree what happens if the trial succeeds. Otherwise, promising ventures can spend months demonstrating their product without gaining a viable contract or understanding the next decision.

    Ukraine’s experience also challenges overly optimistic accounts of innovation. EU4Innovation East identifies fragmented support, uneven access to finance and gaps between technical talent and commercial capability. Its findings suggest that creating more programmes will achieve limited progress unless the connections between them improve. UK regional partnerships should examine whether an entrepreneur can actually move between advice, facilities, investment and customers. EU4Innovation East

    Direct collaboration is already possible. UK–Ukraine TechBridge connects the two technology sectors through activities covering skills, innovation, trade and investment. British firms could explore partnerships with Ukrainian developers around a defined commercial challenge. Such relationships should recognise Ukrainian businesses as partners bringing expertise, ambition and market knowledge, with opportunities for both sides to develop products and reach customers. ukukrainetechbridge.org

    A useful starting point is a ninety day innovation project. Select one problem with a measurable business cost, appoint an accountable sponsor and assemble a small team involving users and an external partner. Set a budget, agree the evidence required and test an initial solution. Review progress regularly, recording failures as well as improvements so subsequent decisions reflect what actually happened.

    The leadership task is to make useful collaboration easier and sustain it through to adoption. Assess progress through changes in productivity, customer experience, revenue or resilience. Ukraine’s strongest examples encourage UK businesses to examine how quickly their own organisations can recognise a need, mobilise expertise and put a proven solution to work.

    References

    1. EU4Innovation East (2026). From resilience to scale: what Ukraine’s startup ecosystem needs next, 6 July.
    2. Ministry of Digital Transformation of Ukraine (n.d.). Diia.
    3. BRAVE1 (2026). Brave1 has awarded more than 1,000 grants to Ukrainian defense developers, 14 September.
    4. European Commission (n.d.). Ukraine bets on research talent and a thriving startup sector.
    5. UK Research and Innovation (2025). Knowledge Transfer Partnership guidance, updated 27 October.
    6. European Innovation Council and SMEs Executive Agency (2025). Ukrainian tech SMEs and start-ups look to EIC for support, 3 December.
    7. UK–Ukraine TechBridge (n.d.). The UK–Ukraine TechBridge.

    Download the editable Word version.

  • Industry 6.0 and Its Transformative Impact on Education

    Industry 6.0 and Its Transformative Impact on Education

    Curriculum & Learning Content– Emphasis on interdisciplinary skills: blending AI, robotics, systems thinking, ethics, sustainability, materials science, data science.
    – Inclusion of advanced topics: generative AI, swarm robotics, quantum computing, IoT/IIoT, digital twins.
    – Focus on customization of learning paths to match rapid technological change.    		Updating curricula takes time; resistance from traditional disciplines; teacher training; resource constraints; risk students are taught tools rather than fundamental thinking.Opportunity for institutions to stand out by offering cutting-edge courses; partnerships with industry for co-designed curricula; online and micro-credentials to keep pace.

    Introduction

    The evolution of industrial revolutions has always reshaped the world’s workforce and educational systems. From the steam engines of Industry 1.0 to Industry 4.0’s digital revolution, each era demanded new skills and updated curricula. Now, Industry 6.0 emerges as the next frontier—a fusion of human-centric technology, sustainability, and ethical innovation. This shift isn’t just about advancing machines; it’s about redefining how humans and technology collaborate to create a more equitable, sustainable future. To prepare for this 变革, education must adapt to nurture the skills and values Industry 6.0 demands.

    What is Industry 6.0?

    Industry 6.0 builds on the automation and AI of Industry 4.0 but prioritizes collaboration between humans and intelligent systems, such as AI, robotics, and IoT, within a circular economy framework. Key characteristics include:

    • Human-Machine Synergy: Smart systems handle repetitive tasks, while humans focus on creativity, decision-making, and problem-solving.
    • Sustainability: Designing products and processes to minimize waste, maximize resource reuse, and reduce carbon footprints.
    • Ethical AI: Ensuring technology aligns with societal values, respects privacy, and avoids biases.
    • Bio-Robotics & Precision Healthcare: Blending biology with robotics to advance personalized healthcare and manufacturing.

    Industry 6.0 isn’t about replacing humans; it’s about elevating human potential through technology, all while safeguarding the planet.

    How Education Will Need to Transform

    With Industry 6.0 on the horizon (or already emerging in R&D/early adoption), the educational landscape must evolve to prepare learners — from school through to lifelong learning — for this new paradigm. Here are key areas of change, along with challenges and opportunities.

    DomainFuture Features / Needed ChangesImplications & ChallengesOpportunities
    Pedagogy & Teaching Modes– More project-based, experiential learning: students working with real systems, robots, sensors, AI agents.
    – Use of AR/VR, simulation, digital twins in teaching: lets students experiment in virtual/augmented environments.
    – Hybrid / blended / remote learning as norm; possibly continuous “just-in-time” modules.
    – Emphasis on soft skills: collaboration with AI/machines, ethics, adaptability, lifelong learning.    		Ensuring access to required technology and infrastructure; teacher upskilling; balancing traditional assessments with more open-ended work; managing equity so all students benefit.More engaging and relevant learning; ability to serve diverse learners; creating lifelong learning ecosystems; closer ties with industry and research labs.
    Teacher / Instructor Roles– Teachers become facilitators, guides, co-learners rather than just content deliverers.
    – Need for continuous upskilling: understanding of latest AI, robotics, sustainability, new manufacturing tech.
    – Ethical and responsible AI in education: understanding bias, privacy, etc.    		Burnout risk; effort needed for professional development; mismatch between what industry needs and what teachers currently know; funding.New roles: AI coach, learning experience designer; possibilities for teachers to engage with industry; improved practices feeding back into education research.
    Assessment & Credentials– Assessments that evaluate ability to solve open-ended, real-world problems, not just rote knowledge.
    – Micro-credentials, stackable certificates, continuous assessment.
    – Badging, portfolio-based evaluation, peer assessment.
    – Accreditation must adapt for hybrid learning, AI tools usage.    		Ensuring credibility; avoiding fragmentation; reconciling standardised assessment vs flexibility; integrity issues (cheating, misuse of AI).More personalized paths; quicker feedback loops; better alignment with what industry actually needs; lifelong learning is easier to credential.
    Infrastructure & Tools– Access to AI labs, robotics kits, IoT sensors, AR/VR gear, simulation / digital twin platforms.
    – High bandwidth connectivity, edge computing, cloud access.
    – Data infrastructure and ethics around student data.
    – Maker spaces / fab labs integrated into schools and universities.    		Costs; maintenance; ensuring that rural / low-income regions are not left behind; cybersecurity; digital divide.Stimulating innovation among students; enhancing hands-on skills; better preparedness for real industrial environments; possibility of remote labs etc.
    Lifelong Learning & Reskilling– Rapid evolution means reskilling/upskilling becomes continual rather than occasional.
    – Flexible learning: modular, part-time, short courses, online or hybrid.
    – Partnerships with industry: internships, apprenticeships, co-op, collaborative research.
    – Emphasis on ethics, sustainability, global citizenship as well as technical ability.    		Motivating adult learners; who pays; ensuring credentials are recognised; keeping content up-to-date; balancing just-in-time learning vs deep foundational knowledge.Huge potential: for those in current workforce to transition; for education to become truly lifelong; economic benefit from upskilling; reducing skills shortages.

    Vision: What Education Could Look Like in an Industry 6.0 World

    To make this more concrete, here’s a possible snapshot of what schooling / higher education might look like in (say) 2040-2050 in a country that has successfully adapted.

    • Elementary / Secondary Schools
      Students are exposed early to AI which is integrated into all subjects. Basic robotics/IoT kits are commonplace. Virtual labs and AR/VR allow exploration of manufacturing, biology, environmental sustainability. Assessment includes portfolios, group projects, and real-world problem solving (e.g. sustainability of local community).
    • Vocational / Technical Colleges
      Strong partnership with nearby factories/labs where students train on real machines, digital twins, predictive maintenance systems. Short, stackable certifications offered on topics such as human-robot collaboration, edge computing, generative design, circular design.
    • Universities
      Interdisciplinary programmes: merging engineering, AI/data science, environmental sciences, business. Research embedded into teaching. Massive open courses / micro-credentials for lifelong learners. Graduates equipped not only with technical skills but with ability to learn, adapt, work across domains, manage AI systems, think ethically.
    • Lifelong Learning / Workforce
      Platforms that allow workers to upskill mid-career: e.g. short courses in autonomous system supervision, sustainability auditing, AI safety. Businesses run internal academies. Governments support re-skilling programs especially for roles at risk of automation.

    Conclusion

    Industry 6.0 promises a future of deeply interconnected, intelligent, sustainable, and highly flexible manufacturing and production. Education is not a side show in this transformation — it is central. Preparing learners for an Industry 6.0 world means more than teaching new technical tools; it requires rethinking how we learn, who teaches, what is assessed, and ensuring ethical and equitable access.

    If we get this right, education and industry can form a virtuous cycle: industry offering challenges and real-world systems, education producing not just skilled workers but innovative, ethical, adaptive thinkers who can chart sustainable progress.

  • Exploring the business model trends for agri-food

    Exploring the business model trends for agri-food

    The food we eat is one of the most important aspects of our lives, besides clear water to drink. 

    In 2020, there are an increasing number of trents which we see in the agrifood market place which are coming together and making us rethink the consumption model for meat and more importantly the entire diet humans consume on the planet. Let’s highlight a few.

    The science behind the types of food we need is changing as we see the standard “post second world war” diet increasingly puts populations into obesity and early death. The understanding of macro and micro nutrients and what a balanced diet is has led to less meat consumption and also the rise of veganism throughout the western world(veganuary). The amount of information (some mis-information) available on good food diets (also sustainable consumption) is rising which allows people to research their own, create personal plans and develop better understandings, leading to a more diverse range of food consumption patterns.

    The welfare of animals requirements is growing as consumers demand better, which is driving up costs, the use of antibiotics and larger farms to maintain profitability. Biosecurity is an issue as Swine Flu, Bird Flu, SARs and Covid-19 all shown this global issue is not going away, so further research and understanding to mandate our food security is needed. The processing of meat is a major issue and the WHO has declared processed and cooked meats a carcinogen. 

    The relationship between land, its value, productivity and product type is reducing as technology allows these connections to be removed. The cost of labour is increasing, costs of health and safety in the (farm) workplace and the continued mechanisation, automation and ultimately robotization/AI replacement is increasing at a faster and faster pace.

    The percentage cost of food per household has over the last 50 years gone down, so consumers are increasingly looking for provenance of their food and understanding the benefits of finding diverse and local sources, through Veg and Meat Box schemes and buying directly. These short supply chains have proved more resilient and sustainable and technologies such as BlockChain, E-payments and direct messaging have proven themselves.

    The cost of carbon used in the production of food has come into public sectiny. Many countries require and industries have to account for the complete lifecycle of their products. Therefore within the agri-food sector this would then bring in creation, processing, transport, packaging and waste disposal which would currently make it unsustainable.

    The western world subsidises food through (In the UK its currently £3.4bn a year through CAP, which is around £56 per person per year which no other industry sector gets (pre Covid-19)) based on a post second world war model. This is based on the amount of land and food groups, which is a broken link to production already highlighted.

    The connection between farms and the environment is currently being explored as the next subside system(post-Brexit). The rural environment has been created by our farming methods and food requirements. These food requirements have changed and are changing fast so will result in changes to the rural landscape. The public’s perception and requirement of the rural landscape is under researched (are they happy with greenhouses the size of a small town or forests surrounding all villages. The options to decrease the environmental impact of the populations activities and their acceptance public debate.

    These trends are making the very business model of food development and consumption change very quickly and it’s important we discuss them as a community.