AI for Orchestrators - Newsletter #22

The latest AI insights for Organisational Orchestrators.

Staccato provocation…

Consider that your cost structure and investment possibilities could look radically different in 9-12 months…

Hello Business Orchestrators!

In this weeks newsletter:

Funding fuels activity. But what happens when those activities are changing at an atomic level on an almost daily basis. From what is done, how it’s done, who can do it, how long it takes…and so on.

Consider how organisations from across the spectrum of public and commercial operations are absorbing cheap, easy to access generative AI tools, often requiring no significant training costs. And powering the discovery of new use cases, flywheels and multiple overlapping feedback loops.

Consider how traditional organisational assumptions, including how targets are set and performance is measured, and fresh approaches to possibility spaces, is simultaneously driving growth across widening circles, whilst causing consternation in others. Sometimes within the same organisation!

Exhibit A: Another McKinsey report stating that employee usage of GenAI is at an inflection point, whilst their organisation lags behind.

Exhibit B: Biggest US companies warn of growing AI risk (FT paywall).

While it would be easy to get hung-up on these kind of headlines, lets circle back to the theme of this newsletter. Business Orchestration, and today specifically how funding mechanisms are about to shift.

First, national and international funding programmes. These are useful at stimulating investment, collaboration across organisational silos, and the acceleration of science. But they are friction-heavy and therefore ideal candidates for applying evolving GenAI capabilities. We will start to see radical time and cost reductions in applying for, and implementing, funded projects. It will not happen all at once, therefore exponential improvements in one part of the funding process, such as funding applications, will generate new bottlenecks in other parts (evaluation, allocation of funds etc.). But it will gradually level out. I discussed the EU’s Horizon Europe challenges here. Within two years, by the time the EU’s next Funding Research Programme (FP10) starts to crystallise, the activities involved in the commercialisation of R&D will be unrecognisable, powered by agent-based generative AI platforms and “AI Scientists”.

Second, the Venture Capital industry is poised for a significant shift driven by advancements in generative AI. As companies, including startups, experience rapid disruption due to LLM-based technologies, predicting successful ventures will become increasingly challenging. With AI reducing operational costs, smaller funds are likely to become more common, and limited partners (LPs) will exercise greater caution. Startups may require less funding and, as a result, gain more flexibility, potentially reducing their dependency on traditional VC constraints. This evolving landscape will necessitate new strategies and ongoing adaptation within the industry. Expect to see a greater shift towards molecules and materials.

Third, the Private Equity industry is poised for significant transformation due to the rapid advancements in generative AI, which are fundamentally altering the operations and activities of portfolio companies and potential acquisition targets. Generative AI is reshaping cost structures, streamlining processes, and enhancing or eroding competitive advantages within industries. As a result, the valuation of target companies could experience drastic fluctuations—both positive and negative—within a short timeframe, potentially as little as six months. These shifts are driven by AI's ability to rapidly optimise operations, reduce costs, and disrupt traditional business models, thereby affecting the strategic considerations of private equity firms when assessing both existing investments and new acquisition opportunities. Expect to see pressure from LPs for greater simulation and predictive capabilities.

Finally, Corporations and SMEs are likely to increasingly favour in-house development over mergers and acquisitions as generative AI enhances internal capabilities within the existing cost structure. The automation of tasks and workflows will allow companies to unlock latent capacity, enabling them to achieve more without expanding their workforce or resources. Additionally, the emergence of AI-augmented scientists and R&D teams promises faster innovation and product development, reducing the reliance on big external acquisitions for growth. This shift will make organic development not only more feasible but also more strategic, allowing companies to maintain greater control and customisation in their growth trajectories.

Now, lets dive into some of the weeks headlines that could be on your radars, dear Orchestrators, as you give me 5 more minutes of your valuable time!

This weeks attention grabbers:

• Sakana AI’s recent paper on the possibilities of an “AI Scientist” is getting a lot of attention. Matthew Berman, in his YouTube channel, gives a good balanced review of what’s unfolding here.

• ElevenLabs AI Reader can now narrate text in 32 languages (The Verge)

• Pattern recognition…pick up a few clues about where scientific research is going at Google DeepMind…AlphaFold3, AlphaProof, AlphaGeometry…

• Paradoxical state of AI: Education and AI - Ethan Mollick .

• Deloitte reports “Enterprises face GenAI scaling challenges”. Square that with the progress individuals and teams are discovering. Perhaps some re-wiring of mindsets, skillsets and toolsets at the top is required (Technology Magazine).

5 Funding questions for Organisational Orchestrators:

1. How are we ensuring that our funding strategies are aligned with the rapidly evolving capabilities of generative AI, especially as these tools disrupt traditional workflows and create new, unforeseen opportunities?

2. What mechanisms do we have in place to identify, evaluate, and scale emerging AI-driven use cases that could redefine our core business activities, and how do we prioritise these against existing initiatives?

3. As generative AI democratises innovation and alters job roles, how are we adapting our performance metrics and target-setting frameworks to accurately reflect the changing nature of work and value creation within the organisation?

4. In a landscape where AI is generating overlapping feedback loops and unpredictable growth paths, how are we balancing the need for rapid experimentation with the risks of strategic misalignment or internal conflict?

5. What steps are we taking to maintain coherence and focus within the organisation as AI-driven possibilities expand, potentially creating friction between established practices and new, AI-enabled approaches?

Staccato Burst…

Continuously re-define “fund”…

That’s all for this week. If you’re curious you can also check out more insights from Gaoithe.biz and the Leading with GenAI podcast, on the organisational implications from applying (or not applying) GenAI.