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The gap between the supply and demand for generative AI-literate employees can be attributed to several factors: ### **Reasons for the Gap** 1. **Rapid Advancement of Technology**: Generative AI has evolved at a breakneck pace, and many education systems and training programs haven't kept up with the speed of change. 2. **Specialized Knowledge Requirements**: Generative AI involves complex concepts such as neural networks, prompt engineering, large language models (LLMs), and domain-specific adaptations, which require a strong foundation in mathematics, programming, and machine learning. 3. **Limited Expertise Pool**: The field of AI is relatively new, and there are fewer professionals with advanced expertise in generative AI as compared to traditional software development or data science roles. 4. **High Demand Across Industries**: As more industries recognize the transformative potential of generative AI, demand for these skills has skyrocketed, leading to competition for the limited available talent. 5. **Education Lag**: Academic programs and certifications often take time to develop and adapt, meaning there are fewer graduates with direct generative AI training. --- ### **How Organizations Can Address This Gap** 1. **Invest in Upskilling Current Employees**: - **Workshops and Bootcamps**: Conduct intensive training programs focused on generative AI tools, technologies, and practical applications. - **Online Learning Platforms**: Encourage employees to complete courses on platforms like Coursera, Udemy, and edX, which offer specialized AI tracks. - **Internal Mentorship**: Create mentorship programs where experienced AI professionals within the organization can train less experienced staff. 2. **Foster a Learning Culture**: - Encourage experimentation with generative AI tools like ChatGPT, DALL·E, or MidJourney for day-to-day tasks to build familiarity. - Provide incentives for employees to innovate and explore AI applications relevant to their roles. 3. **Partner with Academic Institutions**: Collaborate with universities and research institutions to offer customized training programs or internships that align with organizational needs. 4. **Leverage No-Code and Low-Code Platforms**: Provide employees with access to user-friendly AI tools that don’t require deep technical expertise, allowing non-technical staff to integrate generative AI into their work. 5. **Cross-Disciplinary Training**: Since generative AI intersects with various fields, encourage employees from diverse backgrounds (e.g., marketing, HR, and design) to understand how generative AI can apply to their domains. 6. **Build AI Awareness at All Levels**: Offer high-level sessions for leadership and strategic teams to understand the potential and limitations of generative AI, enabling better decision-making and strategic alignment. By adopting a multifaceted approach, organizations can close the skills gap and build a workforce capable of leveraging the full potential of generative AI.

Had good foundational concepts about AI, but I think too many conversational videos with IBM engineers presenting their personal opinions about the future of AI. I found most of them to be overly opiniated with elementary analogies and some even with almost no relevance or value to actual learning about AI. For example "comparing AI > to the > Horse & Buggy" come on really, how about using the "Computer" with modern relevance? Highly recommend replacing one or two of these all-talk videos with some real cool and interesting use case examples showing AI in action. A practical and applied presentation in real world scenarios like technical medicine, industrial production, scientific experiment, etc.

a bit too much marketing, filled with ibm motherhood about productivity, efficiency, and improved customer service. Some technical descriptions failed to properly differentiate between traditional application development and AI application development. Also much of the youve got to have ai misses the point that business use applications and processes to improve performance, these can be implemented manually, traditionally programmed, purchased off the self, or developed with AI. It is the process improvement that matters, alternative implementations need to be evaluated. AI can help with some, not others, but you never choose AI just because it is AI.

My expectations for this cource were higher to be honest. The last asignment for both IBM Cloud and Watson Studio wasn't so clear and informative, but very dry and just "do this and press here...". There was no a signle explanation of how we use these tools and why, and how exactly these work, and which other tools we can use and how. For sure I will continue with the second part, because I'm expecting to learn more. In the other hand the speakers were using clear and simple language and made all the information shared easily understood.

The course material was quite helpful, but following through the assignment was troublesome when there were errors(e.g. selecting the location for Watson servers).

The biggest drawback in this course is in the peer review(not sure if it is Coursera's drawback overall), since one has to 'wait' until someone submits the assignment for me to grade and 'complete the course'.

This should be fixed in the long run, since it really goes against Coursera's policy of 'pay minimum tuition by finishing early'.

Good course but there were numerous errors and issues with content. I reported all except one where there was an audio issue with the videos. In general the sound quality was not the best in the videos. Levels are too low, in general and there was audio that was recorded over other audio during one of the videos. I don't recall which but it was obvious. Other than the technical issues, the content was great, informative, and inspiring.

Most of the course had engaging videos and was quite informative. The ethics segment was interesting and important, however the interviewees seemed monotonous and low energy - like they were reading off a prompt. It made it difficult to focus and be enthusiastic about the subject. There were a few outdated links that I was supposed to click on and led to an error page. I flagged them all, please fix!

The hours calculated to complete this course are not exactly accurate. The method does not include taking notes and having to go through material(s) more than once.

The course could have had some better visual examples.

The course could have offered ACTUAL counterpoints (not just in name) and discussion of those counterpoints regarding A.I. in our lives....(as people are not choosing to do this).

It's a good course if you don't have any idea about IA. It'll give you the most important concetps and the bases to start your own researchs.

Though, the definitios are given by IBM Experts, and they have different concepts by themselves.

It would be great to be homologous in the information and teach a course with set information and not only with a personal opinion by the experts.

If you're truly a beginner with no prior exposure at all, might be helpful information. The "Honors" assignment was an odd cut/paste job that hopefully is being used for some purpose by the course creators, otherwise the only value it might serve is to introduce a chatbot to somebody who has never engaged with one in their entire life, which is probably unlikely this day in age.

Thanks Coursera and IBM for providing this condition for all Enthusiasts.

I'm very sorry that your website does not verify Iranian users,

Your goal is to provide education for everyone,

Why should we, who are interested in education, be influenced by politics?

Isn't education the best way to help deprived countries?

I feel that this policy has no place in educational justice.

The delivery format of interviews, on the one hand, and speech-to-text generated slides is monotonic. The interviewees repeat themselves. There is a strong bias given to the Youtube AI expert. I found the hands-on exercise to be interesting, particularly the graded one with the image recognition. There is lots of extra material provided for continuous learning.

It is a well designed course for AI and suitable for all who need to upskill themselves to domain of ML and AI. I took up this course to understand nuances of ML so as to apply in chemistry. I recommend this course to all irrespective of their field of interest. I did not receive the certificate as there is a big glitch. Coursera must address to this immediately.

1. Очень интересная тема представлена самым неинтересным образом.

2. Для тех, кто плохо знает английский язык и смотрит с субтитрами плохо оптимизирована подача материала и сдача тестов.

3. Последний тест оценивают такие же ученики как и Вы. Если вы плохо формулируете мысль на английском, то получите плохую оценку, которая повлияет на оценку сертификата.

As an engineer, this course seems geared towards training sales and business personnel the very basics of AI ML DS. With the information from this course I learned a few terms, but nothing functional to help me develop models or perform tasks related to this skill. If you're a non-engineer I would recommend it. Otherwise spend your time elsewhere.

The first two weeks are very helpful at establishing a broad understanding of AI. The third and fourth week lacks depth and mostly feels like an IBM advertisement at best and IBM propaganda at worst. Therefore the second part of this course is not really something I would want to pay for. The first part is worth it though!

There were grammar and spelling errors in the deck. The audio in the 3rd module was terrible. It was obvious some of the presenters were reading form a script which was distracting. I would have expected a better presentation, so I am a little disappointed.

Good overview, but the course materials are very hard to focus on (monotonous AI voice) and look surprisingly unprofessional. The badge is not signed directly by IBM, but by Coursera, which in my opinion makes the course less attractive on your CV.

the course data and videos are great no doubt about it however it is the verification process for obtaining the certification for this course which involves face scanning is severely flawed.I havent been able to get my certificate for a long time.

Las mujeres aparecen casi únicamente (apareció una antes menos de 30 segundos) para hablar de ética, de diversidad e inclusión. Como enseña el curso, los bias que tiene la IA nacen de los huamnos. Acá, evidentemente los hay.

The content feels more like an advertisement for IBM or AI in business rather than a structured course. Additionally, there is too much repetitive information, which reduces the overall effectiveness of the material.