Scott Hebner’s Post

Interesting McKinsey & Company article on the impact of #generativeAI in the agricuture industry, one of the industries with the lowest adoption of #AI to date. This is especially true in the R&D and agronomy domains. The #agricuture industry sits on enormously large and complex data-sets that are largely untapped in terms of potential asset value. As the article spells out, using AI to help farmers manage crops yields can produce a massiven return estimated to be over $100B in impact. While the focus of this article is on #GenAI, this only sets the stage for new agricuturual AI use cases powered by the advent of #causalAI. The science of "why" and #causality will advance the correlative nature of today's LLMs/GenAI approaches into the world of cause & effect, which in turn, will revolutionize problem-solving and crop optimization techniques in this industry. This includes things like root causes detection and the ability to apply interventions, counterfacturals and confounding variables into "what if" scenario planning. As they say, every effect has a cause but you should be very careful about assuming correlative outcomes from LLMs = causation. #causalAI will unlock the ability to analyze and perscriptive act in totally new ways. If interested to learning more, feel free to contact me.

Congratulations to Index for being recognized in the 29th overall spot in the Financial Times fastest-growing businesses in Europe. As I have written previously, the gap between #AITalent supply and demand will only widen in the years ahead. The Index on-demand talent platform makes it much easier to identify and hire top talent and to start up new #AI projects with minimal risk. This is why they are experiecing a 226% CAGR and very high quality ratings. If I can help you with your AI talent needs, please let me know and I can help connect you as appropriate based on your needs. https://lnkd.in/edhBWy3U

This study by McKinsey & Company on the growing importance of #ProductMarketing (PMM) is worth a read, along with the insights from one of the best product marketing leaders on the planet - Liz Urheim ! Its message is especially relevant in today's race to establish leadership in #AI software within a marketplace that is very much in its infancy. I couldn't agree more that the multifaceted role of the PMM is poised to become a differentiator for the most successful software companies. As referenced, among the top 100 companies, those growing the fastest have a 30% higher rate of PMMs. And it's also true that these roles are hard to find as it requires a strong technical and business acumen that only comes with experience. The lesson I learned throughout my career is that organizationally sequestering product marketing from the core business and its product management function is highly counterproductive. PMMs / PMs should be viewed as two sides of the same coin - collectively the "Hub" in the "Hub and Spoke" model of software go-to-market models. In fact, I remember the days when they were part of the same organization, and that is when growth was the strongest. The key message -- don't view the marketing function as only a "demand generation gear box", but also as a critical component in your product lifecycle management and how you orchestration your go-to-market model in today's #SaaS driven world. #Marketing #ProductManagement #Software #BusinessManagement

The attached editorial on #AI colonialism by Dr. Seth Dobrin is quite insightful. While today’s #generativeAI models are dominated by a few, it’s my view that while these holistic “one size fits all” models will always be of value, the emergence of a thriving ecosystem of specialized models is inevitable. Why? Well, the need to: (1) capture the unique language and knowledge of a business (2) instill explainability aligned variable conditions, policies & regulations (3) reduce business-specific bias, hallucinations & false influences. (4) infuse causality and the science of “why” to truly problem solve (what-ifs). These share a common attribute - an uncountable array of domains and use cases. And thus, the need for a fully open ecosystem of “building block” models. Seth’s points are right on and we should all think about how we collectively remedy these concerns. ———-

This PoV from McKinsey & Company is right on. AI is still in its infancy. In my view, #5 is the next big advancement in #AI for Business, as today’s models lack any true ability to reason or make decisions. Thus, no real ability to intervene, test counter-factorials, uncover confounding influences or evaluate various “what-if” scenarios - i.e, problems-solve. Casual AI — the algorithmic science of causality and why things happen —promises to change this! Read more on its pending impact here: https://lnkd.in/efbt5zrD ———-

It's expected that the supply and demand gap for experienced #AI skills will expand from today's 2.3x to over 4x in the years to come. Its time to act, and act quickly to secure the skills you'll need. Check out the "#GenAI Hiring Guide" from Index - a pioneer in helping orgs quickly and flexibility source AI & SW talent. As an AI advisor to Index contact me if I can help you explore the available talent pool. Also, read more about the turbulence in the AI talent marketplace here: --> https://lnkd.in/ea89VBNy #GenerativeAI #CausalAI #AITalent