The AI Genie is out of the lamp, it will never go back in so we better make those wishes responsibly
views are my own
Recently I had the pleasure of attending a Prompt-a-thon. You've heard that right, they might not have existed a few months ago but they are a thing now??
This was an innovative event hosted by Microsoft's team Elena C. , Tatiana Arventi , Kris Wilson who brought together the excitement of a hackathon with the transformative power of M365 Copilot. It was a day brimming with creativity, problem-solving, and collaboration that brought a couple of "aha moments"
The Prompt-a-thon was an exceptional opportunity to learn from industry peers that have access to M365 Copilot within their own organisation. We delved into best practices, shared our insights, and collectively explored new strategies to maximize the value of Copilot. The atmosphere was electric, with ideas sparking from every corner of the room as we worked together to solve complex challenges.
On that note, it is my absolute pleasure to give credit to our amazing Modern Workplace team Jo Brown , Gill Glover , Suzy Molloy & Nicole Stevenson as without them advocating for our early access programme last year I wouldn't have been in a position of becoming a Power User. This early access to M365 Copilot has been an absolute revelation for me. As one of the first to dive into its depths, I’ve become an expert user, a journey that is both exhilarating and deeply rewarding.
The other attendees took notice during the Prompt-a-thon of multiple use of advanced prompts; they saw how naturally I interacted with Copilot, turning complex prompts into elegant solutions. It was refreshing to be recognised for my proficiency (I know I know I'm not very modest), and it encouraged a lively exchange of ideas, with many eager to learn how they too could enhance their work.
And here is where the penny drop moment occurred, which I want to share as the AI industry and it's 10x velocity is fundamentally different from any before. If organisations are to thrive they should take into consideration the following:
1. Invest into internal R&D as opposed to off-the-shelf solutions from consultants
The field of technology boasts approximately 30 million developers and 300,000 machine learning (ML) engineers, yet the number of ML researchers is markedly lower, estimated at 30,000. Within this exclusive sphere, those pioneering the cutting-edge of ML research, particularly in the development of advanced systems akin to GPT-4 or Claude 3, are exceedingly rare. It is estimated that cca 100 researchers worldwide possess the expertise to construct such sophisticated AI models.
So what can we conclude ? This is fairly NEW for everyone (or the majority) and the typical one size fits all solutions provided by consultants will fail short as they do not have that knowledge to make AI work for the organisation's needs or even an overall AI strategic approach (although many will wrap them up in a nice shape of a "talk to a customer service bot" or "interrogate your data")
That is why companies must bring at the forefront their internal workforce and encourage hyper experimentation. Those colleagues will be very aware of the organisational context. their problems and are in the best position to experiment with AI to find powerful use cases.
2. Encourage transparency of everything and stimulate employee engagement
Very few organisations hired people 2,3,5 years ago based on their AI skills so the capability can be anywhere, and that creativity of how to best leverage AI can be found on any layer of the company.
We know from media that originally various organisations (JP Morgan, Apple, Samsung) restricted ChatGPT use, mainly due to data leak concerns, however that had a small effect as the employees once they realised the productivity gains they started using the tools from their personal mobiles and found work arounds but did not openly admit it.
领英推荐
This approach of stealth tech encourages employees to remain reticent about their innovative contributions and the enhancements in efficiency they achieve so the competitive advantage for the organisation is lost.
Companies should encourage and celebrate any AI user that have identified opportunities to streamline workflows and come up with innovative use cases, this could be represented by substantial rewards such as work from anywhere or unlimited unpaid leave (wink wink) or any other form of incentive that demonstrates a true commitment for ground breaking AI ideas pushed into execution.
3. Make it real, don't just include the Art of the possible, focus on the applied AI
I can attest openly that in Dec 2022 I had zero knowledge on the difference between AI, ML and Deep Learning or a clue of what RAG means beyond the Red, Amber, Green ?? used in Project Management. Having for the very first time access to a tool such as M365 Copilot encourages exploration and stimulates curiosity.
I can say that the honeymoon phase will usually be over pretty quickly if the focus is just on theory. No amount of online learning, or virtual courses will help with employees upskill at the fast pace that is required. The optimal approach is to provide them with something tangible, and high level guidance. Rest assured people will figure things out by themselves on how to streamline tedious parts of their roles and benefit of that sweet reclaimed time.
This is one way to see tangible benefits from GenAI and upskill workforce in the filed of LLMs & SLMs
4. The C-suite AI Officer
As the idiom goes "no man is an island, entire of itself", and therefore each organisation should consider a hub and spoke model, similar to a Enterprise wide Centre of Enablement, led by an AI Officer which will hold the pen on the AI roadmap for the entire company.
Too often strategies get segregated and each division would go on various paths, exploring in isolation. There is a need for someone to join the IT, with HR with operations and overall end to end workflow. At least for now that would be the best way for companies to benefit by applying a principle of AI Systems Thinking and joining this up at scale.
As an agilist at heart I believe firmly in the concept of Shu (initial novice stage) Ha (mastery-level self-organising) Ri (transcendence), so the model will for sure evolve in time, however given we're just at a novice stage we should leverage those connections as much as possible and benefit of cross team knowledge share and pollination.
Thank you so much for reading my blog, and to wrap it up I'll share top 3 moments from the AI space this month:
Senior Agile Coach - Consultant at Contino
5 个月Great article as the Agile commuting also need to evolve with the evolution of thinking and tech. We'll defo see more uses of AI in various of aspects of our lives in the next decade. We'll probably see a raise of an ethical AI as it also can open a can of worms if companies don't implement AI responsibly and ethically. It'd be interesting to see what he next few years bring. Only time will tell ??
Senior Adoption & Change Consultant for M365 apps with specialism in M365 Copilot
5 个月Fantastic article Victor, thanks for being one of our key Copilot influencers in our EAP
Graduate Business Analyst at Cognizant
5 个月Insightul post Thanks for sharing The AI is evolving so rapidly I wonder where we’ll be in 6 months time
Modern Workplace Product Owner at Lloyds Banking Group
5 个月Great article Victor, you have embraced the new technology with a growth mindset ??.