The 8 DOs are related to Talent, Culture, Data Readiness and Governance and follow the following formula:

AI Effectiveness =Talent X Culture X Data Readiness X Governance

The DOs are about how to initiate, plan, design and implement AI systems.

Clearly defining how AI will impact or transform your business, solving real business challenges with measurable outcomes with ROI and building a complete AI ready organization, starts with pilot projects and then implementing scalable AI solutions across the organization.

Here we will address only culture and data quality as these 2 factors are responsible for the majority of AI implementation failures. As above 70% of AI transformations fail the attached AI pitfalls and challenges must be taken into account in the necessary for success prior change management process.

How do you exploit global opportunities and manage challenges in times of uncertainty?

In 2024, the Nobel Prize in Economics was awarded to Daron Acemoglu, Simon Johnson, and James A. Robinson. In a nutshell, their findings show that countries which promote broad participation, secure rights and the rule of law, are economically more successful longer-term than those who concentrate power and wealth among an elite, hindering development.

Although each of us learns through different ways (Reading, Watching, Listening,..) learning by doing is one of the most effective ways. In this article I describe the leadership and other valuable lessons from a real life complex turnaround and M&A project in the technology industry. It is very relevant for the 21st century business world where many start-ups and established companies collaborate to innovate. For obvious reasons no names or locations will be mentioned.

The post discusses the transformative shift from Software-as-a-Service (SaaS) to Agent-as-a-Service (AaaS), highlighting the impact of AI agents on the SaaS industry. It begins by noting the historical evolution of SaaS, which started as a time-sharing model on mainframes in the late 1960s and became the standard for software use at the beginning of the new millennium. However, the landscape is now changing with the advent of AI agents, which are reshaping the industry.

Deepseek was founded approx 2 years ago, has 200 employees, and has invested approx $5 million to develop their innovation. In contrast, OpenAI was founded 10 years ago, has around 4,500 employees, and has raised $6.6 billion in capital. Deepseek is a customer of OpenAI and could scrape their data.
Deepseek disclosed that they used a process called distillation using the Llama open source model to develop their model by asking hundreds of thousands of questions and analyzing the answers.

Many LinkedIn members follow the wind. For 2 years Generative AI would take the world was the motto.

The last few weeks or months the wind has changed and there are clouds in the horizon.

The question is what is the truth of the matter?

Until the 1970/80s the hashtag#research was done in the corporate labs (AT&T, Bell Labs, Dupont, IBM, hashtag#Philips (In the 80s, 6000 PhDs and Scientists in research), Siemens,..), government labs e.g. DARPA in the hashtag#USA and they created innovations like, hashtag#Semiconductors, Radar, hashtag#Nuclear Power, New materials, hashtag#Internet, hashtag#Software, LED, Telco & hashtag#Mobile revolution resulting in companies like Intel, Apple, Microsoft, Amazon, Alphabet, NVidia, ASML, Tencent, Alibaba, that are still driving the economic growth.

How do you Know a Company is Ready for AI?

What are the Steps to Become One?

As AI/Generative AI is the talk of businesses, universities, schools and daily life, many companies are asking:

A. Am I ready for AI and what do I need to have in place for success?

To answer this question please consider the following:

0. THE MOST IMPORTANT: Every company needs to FIRST identify Important Business Problems that AI can enable Solutions easier, cheaper, more efficiently or increase of revenues faster/better than manual or less automated processes. You do not apply AI for the sake of AI.

Large Language Models (LLM) where generative AI belongs are trying to model the human brain with benefits increasing productivity of analyzing or writing text or creating pictures and/or video. Goldman Sachs believes that it will eliminate 300 million workers.

There are many applications (see picture) and the question arises how does it work?

1. Everything starts from a Big Purpose: Generative AI can help you to find the right purpose for you and your company.

2: Compose the Right Team with complimentary competences, commitment and good chemistry among the team members.

3. Work to build a Business Model suitable for the Purpose

How to Build Great Startups the Coming 10 Years

The article is focusing on 2 very important stages of the Startup journey:

1. Customer Discovery

and

2. Customer Validation

It describes step by step all necessary planning and execution activities of a startup journey to ensure the startup belongs to the 5-10% of the startups with successful exits and impact. It also stresses what are the Key principles of success.

Do you have the Culture of Fast Scaling?

Successful leadership follows a number of principles that are the same and independent of where they are applied. Indeed, leadership is about people and leaders need to understand well key aspects of human skills and behaviors. It is people that either create or destroy value and it is essential to know how to lead to create value.

CHATGPT Benefits & Energy Consumption

As the whole technology world is talking about CHATGPT the attached file explains what it is and it's benefits. Companies need to join and integrate such platforms otherwise they will be left behind to put it mildly. What we need to solve with the current AI applications that are using deep learning technology, is that they consume too much energy. This needs to change otherwise we boycott the planet earth sustainability.

This is the 1st post and more will follow:

While we all need to support various pro environment actions like:

- Reuse more

- Recycle more

- Change to electric car

- Eat less or stop eating meat and switch to vegetable based diet

- Reduce food waste

- Support companies with Sustainability driven business models

the sad story is that the 2050 net zero target or max rise in temperature of 1.5 degrees C can never be achieved. Why ?

What are key corporate sustainability trends?

Growth Mindset & The impacts of Xponential Growth

Why are some companies able to create ‘blue oceans’ of uncontested market space while others struggle in ‘red oceans’ of intense competition? To answer this question, we need to look at some examples from a range of industries and identify the specific strategic actions blue ocean companies took to achieve profitable growth. We’ll examine blue ocean strategy examples from the tech, healthcare, fintech, and retail industries and a classic blue ocean example from the entertainment industry. We’ll also take an in-depth look at how one company made the spectacular transformation from the red ocean to the blue ocean.

Since 1995 the Internet, the exponential growth of Computing Power, Digitization, Bandwidth and lower transaction costs as well as exponential decline in Storage costs enabled decentralization of innovation. Consequently the successful established firms of the present and future will innovate together with the Start-up and Scale-up ecosystem. Established companies start to understand that they need to change or they will get beaten by leaner and faster competitors.