2024 – The Year of Big Learning – AI Skills

How can we most effectively acquire personal and professional business knowledge and skills in the field of AI and where and what should we get trained and certified for to start or build on our professional path?

SwissCognitive Guest Blogger: Zhaklina Zhikova – “2024 – The Year of Big Learning – AI Skills”

How can organizations most effectively implement training in AI skills to engage and retain their people and achieve the goals and business impact they have set for themselves? How to tailor AI training to be most effective, targeting specific professional skills and organizational levels? Along with professional technology training, the overall culture in the organization and the “feel” and “sense” of AI are essential, as well as building trust in AI embedded in an organization’s strategy and communication.

These are some of the most seemingly “clear” issues for which there is already a large amount of information, detailed comparisons, and assessments from reputable and professional sources, but behind which practical, methodical, and long-term efforts that are worth making. The purpose of this overview is to save time and effort on initial research and to share experiences from experts in AI training, which can be another direction in the decision tree on this topic in organizations.

AI training is a crucial component in organizations’ strategies, playing a significant role in shaping their future.

According to McKinsey, among the top eight key priorities of CEOs for 2024 are – The challenges of leveraging generative AI in business operations, scaling its applications, and providing a competent advantage through technology to extract maximum value from digital transformations. Over 80% of companies globally are aware of the current and future skills gap related to AI. For over 60% of employees, training in new skills or upskilling related to analytical and creative thinking using AI and big data will be required. Organizations need to prioritize these skill areas to develop employees to their full potential.

Where is AI training used in organizations’ strategies?

Providing broad AI training at all levels – from managers and department heads to CEOs through to all employees – to get a “sense” and knowledge of AI is a crucial step for a successful AI transformation in the company. This goes hand in hand with starting and executing pilot projects early on, creating an internal AI team, developing an AI strategy, and developing external and internal communication with all stakeholders in the company.

The areas of AI training are vast, and most platforms and training opportunities are focused on directions like data scientists, machine learning engineers, AI researchers, and AI enthusiasts.

Image: Datacamp

What route in AI training should we take?

To start our journey in AI learning, it is good to have clarity and a prepared “roadmap,” even when starting from scratch. Examples like this are well-developed with most external online learning platforms. The basic roadmap is prepared according to the learner’s interests and pace for an initial period of 3 to 9-12 months. Aligning the program with the professional goals and depth of learning in the different domains is essential.

It starts with Basics/Fundamentals, building up with specialization and advanced options, developing special AI skills, and learning essential AI tools and packages – tools for various business functions such as marketing, sales, data analytics, customer service, and their practical application. It follows training in additional specializations according to the professional field, certification, constant updating of information and trends, joining professional communities, exchange of ideas and experiences with AI professionals, and last but not least, applying the ethical aspect of AI. It is important to note that an introductory course on AI Ethics and an ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) course, which teaches how to apply AI responsibly and by the new ISO standard, are now included in almost each platform. ISO/IEC 42001 is the first international AI Management System Standard that specifies the requirements for creating, implementing, maintaining, and continuously improving an Artificial Intelligence Management System (AIMS) in organizations.

When an individual creates a learning plan, it defines an indicative timeline, skill goals, activities, programs, and resources needed to achieve those skills. What is our level of knowledge about AI beginner? Do we have a foundation in math and statistics skills? Are we familiar with basic concepts? What is our goal for the training – a new job, a career, or to complement and build on our current career? How much time can we devote to training? What budget can we spend? Do we want to invest in a boot camp, enroll in free courses and videos, or participate in professional online courses? How do we want to learn – in a comprehensive certification program, a Boot Camp, self-paced learning, or various online courses?

How should we prepare to learn best and apply AI learning?

To choose a directed professional focus, what has been required for the

professional role, what skill set is needed, and what level in AI learning do we start from;

To arm ourselves with patience and an understanding that this training is a life-

long process, with time to study each concept for as long as it takes to understand it and move on to the next;

To apply the skills in practical projects to gain practical experience according to

the specific field;

To join the AI community, professional groups, and specialized meetings online

and offline;

To keep learning and building on what enhances our qualifications

and transforms us from novice to expert. To be persistent, patient, and practice;

To review and evaluate the results of AI tools as they;

are there to help us, not decide for us, and to be aware of the ethical aspect of AI.

How do organizations train their employees in AI skills?

According to a Deloitte study, the shift in skills requiring employee training and upskilling concerns the increased value and importance of technology and human-centric skills.

Image: Deloiite

GenAI is to increase the value of some technology-centric and people-centric skills as follows – of the technology-centric abilities, the most significant increase in value is expected for data analysis (70%), prompt engineering (60%), information research (59%), and software engineering/coding (57%). Of the human-centered skills, the most outstanding value is in critical thinking and problem-solving (62%), creativity (59%), flexibility/resilience (58%), and the ability to work in teams (54%).

According to experts, some of the challenges in AI training are adapting training to the extremely rapid and dynamic development of technology, engaging and retaining employees and overcoming resistance to new technologies, respecting ethics and privacy, fostering a culture of continuous learning, and providing hands-on testing and simulations.

Some companies rely on e-learning and outside sources, and also create small internal learning and training communities that allow employees in a supportive atmosphere to experiment, make mistakes, and practice under the guidance of technology-savvy colleagues and instructors, with time set aside for internal discussions on the topic. Before specifying the training itself, it is necessary to identify the areas where GenAI has the most benefit and impact, identify the fully automated tasks, train Managers early, and focus on the application of GenAI so that they can confidently lead their teams and prepare for the risks and opportunities in implementing AI in the company. Best practices include creating Prompt libraries and resources, templates, and successful case studies’ lessons.

To help their employees, some organizations have created so-called “AI Playgrounds”, which contain software, domain-specific data, and policies that enable technically and non-technically oriented employees to experiment with GenAI in a safe environment. This avoids the risks of using external computer servers or violating copyright law. When using externally or internally developed resources for GenAI training in organizations, experts think that e-learning courses have an essential role to play. Still, they may have a limitation because they become obsolete with the rapid dynamics in GenAI development. This type of courses can be the basis for specifying own training in the company and according to industry needs. Collaboration with universities that develop programs for employees of a specific organization that creates GenAI boot camps is often very fruitful.

Many companies take advantage of the vast GenAI learning resources available from external providers with a huge interest in tech courses and training, such as Udemy and edX. For a better learning experience, it is good to combine training in different environments – digital and in-person – with an instructor.

Big tech companies are actively promoting free resources and certification programs for tech and non-tech beginners and experts. Amazon created and launched a free program, “AI Ready” to support professionals in the workplace. Eight new, free AI and generative AI courses will train 2 million people by 2025. The program is dedicated to beginners and experts, covering foundational to advanced AI skills. Microsoft and LinkedIn offered an extensively free Certification and AI skills training program via the LinkedIn platform, with free access until 2025. The initiative is dedicated to training employees globally to understand and be up-to-date with AI, work successfully and confidently with AI, and use GenAI to increase productivity and efficiency in companies while using technology responsibly and ethically. Google provides many free AI Skills courses and AI Skills courses on the Coursera platform.

AI Training – top priority training in organizations

To successfully train and implement AI Skills in an organization, we need to have a focused strategy and policy and internal standards on AI implementation; have goals and be able to measure the impact of AI and its benefits; share successes across our organization; ensure ethical use of AI; develop training plans across the organization and all departments – for those early AI adopters, as well as for those who will be trained later, for department heads to develop plans for their teams.

Demand for AI skills will continue to grow, so organizations need to train and “sell” their people on AI skills training and practice by building a long-term AI strategy across the organization, a continuous learning setup, effective communication, and the right training programs – a roadmap, a mix of established external providers, and dedicated internal learning communities, according to specific tasks and roles within the company. AI training is an investment that will prepare and equip people for the future. Like any investment, it also needs to be measured for its effect on the organization according to the KPIs set for AI’s impact on the business.

About the Author:

Zhaklina Zhikova, PMP, Business professional, with valuable experience in managing dynamic business projects (B2B – Sales, Manufacturing, BPO DACH) in EU companies with the highest technological and business standards, active “agent of change” dedicated to the synergy of AI Success and Business Models.