Funding Squeeze...

Translation...we need to squeeze better returns from existing funding. For Europe to be able to keep up with Asian (not just Chinese) and American RD&I, we need to also focus on how we spend funds. Right down to project and task level. Much oxygen is spent on comparing budgets of billions. In reality, much of that funding goes on project and bureaucratic fat that can be removed. Your time's valuable so lets dive in:

1. More of the funding for the project/initiative can be allocated to the actual science and commercialisation. That goes for project proposals under construction, those already submitted and being evaluated, and those already funded and underway.
2. At least 25% on a rolling annual basis can be shaved from the management (administration/reporting/coordination) costs by using...
3. ...powerful, cheap, evolving GenAI capabilities in the hands of research, business, financial and policy artisans. These can achieve dramatic performance improvements in time, cost and quality. As agent capability gets built into more of the LLMs, we will be able to automate more of the manual activity, elevating teams time and effort towards more creativity...and more projects, more science, more commercial and economic growth.
4. Ideation, iteration, getting feedback and consensus on project scope, especially for European consortia across research and commercial entities, can be cut down from months to weeks, and in some cases days. You would be amazed what can be achieved by artisans from across a consortia harnessing, for example, Zoom/Teams + ChatGPT4o (or whatever LLM you prefer) + Miro + gozigzag.com + Canva. Rapid acceleration on decisions, rewiring budgets, missing pieces to the partner puzzle...all up for grabs. There is friction and percentages everywhere. Same opportunities go for projects under way or proposals under construction. All critical paths can be challenged.
5. Current "state of the art" (SOA) is a key challenge for proposals and projects underway, because it's a moving target, and different people have different opinions on it. Much time, effort and cost is spent trying to figure it out by trawling through research papers and websites, leveraging human expertise etc. But there is a vast source of up to date data in YouTube, and that can now be analysed rapidly with ChatGPT and video summariser GPTs. Checkout min 35:30 on the Leading with GenAI podcast for one of the many ways to exploit YouTube insights (https://www.youtube.com/watch?v=kv2CCxP3XLY) to accelerate activities.
6. Coming soon...scientific, mathematical and simulation AI capabilities that will also accelerate the science and business model aspects of funded projects (AlphaFold3, AlphaProof, AlphaGeometry2, Sora world simulation tools etc.). Get ready for this by getting into the groove with what's already available.
7. Commercialisation/exploitation of funded projects; we need to, and can, get our R&D out into the field and test it earlier. We need faster feedback loops. The biggest problem is friction and bottlenecks. As much of our RD&I is distributed across silos in different organisations and countries, then that is a great place to focus on for applying generative AI.
8. All of the above means that project baselines and the amount of funding needed will continuously be reset as we augment more of our activities with AI/agents.
9. Note: often in consortia, organisations have different standards and rules about what tools they can use. These will evolve under pressure from their own users and market pressures. But bake into your assumptions that there could be an uneven spread of generative AI capabilities. Where there is, mitigate with practical workarounds.
10. It's not about cutting cost...it's about reallocating cost to where it should be; the science, development and commercialisation. Challenge all working assumptions about jobs/and tasks to be done on funding projects. Mainly on how they can be done.
11. There will be people and organisations who will resist. Often they will seek to make their arguments as abstract as possible. Get round this with live demos challenging the foundations of their objections with generative AI powered by your own artisanal mindset, skillset and toolset. Get stakeholder support from partners and executives who can clearly visualise the benefits of your approach.

There's a lot of funding out there. Much of it just needs to be repurposed towards accelerating the scientific and commercialisation aspects of the projects and initiatives.

Unsure how to find significant performance improvements in RD&I funding? Give me a ping and lets have a conversation...