In the ever-evolving landscape of learning and development, Dr. Raman K Attri stands as an expert, guiding organizations through the intricacies of AI integration. As an award-winning Chief Learning Officer (CLO) and a luminary in the realm of accelerated professional and organizational learning, Dr. Attri’s insights have earned him accolades such as Chief Learning Officer of the Year and a spot among Brainz Global 500 Leaders.
With a background in electronics engineering and over two decades of experience, Dr. Attri has not only witnessed but actively contributed to the transformative journey of artificial intelligence. His latest publications, “Chief e-Learning Officer in the Era of Speed” and the upcoming “Chief Learning Technology Officer in the Era of Speed,” provide a roadmap for learning leaders to stay ahead of the AI curve.
We recently got a chance to meet Dr. Raman and delve with him into perspectives on accelerating learning in the age of AI, the changing landscape of workforce development, and the crucial role of human-oriented skills in tandem with technological advancements. Here’s how the rendezvous looked like!
- Can you share the inspiration behind your focus on accelerated professional and organizational learning in the era of speed and AI?
I am highly passionate about learning myself and also to teach people methods and techniques to learn better and faster. Personally, I have earned over 100 international credentials in education, training, and learning domains, besides holding 2 doctorates in strategic organizational learning.
However, my passion for learning is rooted in my backstory. When I was 6 months old, I lost my ability to walk due to a permanent disability. I continued to experience the inability for several years until I found that I had the luxury to sit and learn anything I wanted. As the years passed, I honed my ability to learn through experimentation and mastered the art and science of learning faster. That turned out to be my lifesaver skills.
When I stepped into the professional world, I realized that most employees, peers, and leaders have not been taught this vital skill to learn better and faster to deliver workplace performance. So, I decided to take up my doctorate research on speeding up time to proficiency to understand proven strategies that could accelerate workplace learning, employee performance, and leadership development at the speed of business. I also realized that such strategies were limited to some good organizations only. Therefore, I set on a mission to generate exclusive thought leadership on accelerated organizational learning by authoring over 30 books on this subject and speaking at leading conferences.
Being an electronics engineer by background, I continued to explore how to leverage technologies systematically to ensure speedier development of employees to keep businesses ahead of the technological curves. As a Fortune 500 leader at a hall-of-fame training organization, I spearhead discussions on AI integration in L&D processes. I aim to coach CHROs and CLOs with speed-savvy leadership skills to keep their organizations competitive.
- In your latest books, you outline strategies for learning leaders to stay ahead of the AI curve. How do you see the role of Chief Learning Officers evolving in the face of rapid technological advancements, especially with the integration of AI into business processes?
The technology-driven success of many organizations during the pandemic has proven one important thing: The learning leaders need to be highly strategic when implementing revolutionary, untested, state-of-the-art technologies. However, this strategic thinking does not come easy because learning leaders need to address a gamut of operational and business KPIs. At the same time, technology decisions need to be made in light of its ability to speed up employee development and performance.
Historically, learning leaders have left such strategic decisions to their IT departments. That model may not work any longer. The CLO’s role is becoming crucial and impactful while being in the driver’s seat in making and dictating technology selection and implementation decisions.
Any organization has only one CLO who is perfectly positioned to ensure that an organization’s learning technology strategies are truly strategic and built for speed. They need to understand the science of speed in the context of new technologies and critically examine how these technologies could accelerate employee development and shorten organization’s time to market.
The future of work is being debated with the emergence of AI. The business leaders are getting ready for a deeper level of AI integration in every walk of business. CHROs and CLOs are in a race to figure out not only how to integrate AI into their work processes but also how such integration would impact the future of jobs, skills, and workforce. My latest book, Chief e-Learning Officer in the Era of Speed, and the upcoming book, Chief Learning Technology Officer in the Era of Speed, are based on research with over 50 large organizations, documenting the potential of revolutionary learning technologies, LMSs, AI, AR, and VR. In these books, I have explained a framework and strategies futuristic HR and L&D leaders must implement to accelerate their workforce development faster than the AI curve.
- With your background in electronics engineering, you predicted the trajectory of AI over 28 years ago. How have you seen the industry change, and what do you anticipate in the years to come as AI continues to evolve?
Yeah, that’s right. AI is not a recent phenomenon. It has been here since the late 1990s. It has been taught as a subject in electronics and computer engineering degrees for over three decades.
I remember presenting my project paper on artificial intelligence during my engineering degree program some 30 years ago. Back then, the models and algorithms were rudimentary. The AI technology existed more in engineers’ imaginations, like ‘What if it was possible.’ However, as engineers, we knew what to expect from this technology when it matures. We thought technology would ramp up faster. But it has taken almost three decades for this technology to reach the level where it is today.
Just like other technology leaders, I have witnessed OpenAI’s ChatGPT or Google’s Gemini making a significant leap compared to historical innovations in this technology, which has taken the industry by storm. The primary reason has been the advanced natural language processing capabilities used by the latest AI technologies.
The way I think, still, there is a long way to go as far as the scope and impact of this technology are concerned.
GenAI and assistive apps are certainly creating a lot of buzz. However, AI’s true scope and impact are more extensive than GenAI, software, or apps you know today. The AI models are being embedded into devices, gadgets, and other technologies. Examples are endless: smart glasses, AR/VR, mobile phones, workplace monitors, industrial sensors, disability assistive devices, car navigation systems, vision-based AI, and IoT devices. Such devices, machines, and equipment equipped with AI would perform unimaginable functions without user intervention. This means the work processes using new technologies, devices, or other automation infrastructure will change altogether. What is being done today using manual or human intervention will change forever. Employees either need to learn new skills or they need to learn an entirely new ecosystem to perform their work.
- The impact of AI on jobs is a topic of concern for many. Could you elaborate on your perspective regarding the redefinition of existing jobs and the emergence of new roles in the AI-integrated workplace?
Agree, that the impact of AI on jobs, skills, and work processes is of prime concern to leaders and employees alike. However, we need to see it from the lens of the cyclic nature of technological innovations. The closest similarity to the AI revolution is the revolution created by PCs and the Internet. Didn’t we have similar cynicism and criticisms at the emergence of those technologies? We all expressed shock and surprise at early demonstrations and raised alarms about potential misuses, but finally, we became over-dependent on them. While there were speculations about massive layoffs or job losses back then, you all know that PCs generated billions of jobs.
In my view, AI will follow a similar trajectory this time. Just like the PC technology revolution, AI holds the potential not only to redefine existing jobs but also to discover new jobs.
As we charter the path ahead, we will see a deeper integration of AI into business processes. This could lead to two workplace changes: First, the redefinition of existing jobs rather than replacing them, and second, the emergence of new jobs to support redefined processes.
The first transformation in terms of redefinition of jobs is emerging in 2024 in two sets of jobs. The first set of jobs is where AI-driven automation can replace repetitive, mundane, and time-consuming tasks. These jobs are administrative, backend, support, design, and even blue-collar jobs.
The second set of jobs where redefinition could impact is high-end complex jobs that involve skills such as data analytics, predictive analysis, forecasting, modeling, data mining, financial analysis, and data-driven decision-making.
However, we need to be mindful that this redefinition requires the availability of powerful AI-driven models that could be applied seamlessly to corporate infrastructure. This integration would lead to new jobs such as AI backend infrastructure development jobs to automation and productivity solutions.
The second workplace change in jobs is in regard to the emergence of new jobs. Given AI’s ability to navigate vast amounts of data and produce workable knowledge, the demand for decision-support professionals and knowledge management analysts will increase. Suck folks would have the skills to analyze the knowledge consumption processes and model the AI to best serve the executive and functional decisions.
For instance, interior design and architecture design-related jobs have already shown potential for redefining due to the convergence of AI and AR. This could lead to the emergence of a new set of AI/AR-driven design jobs as the customer would demand highly immersive and realistic views of their homes or offices that exist only on paper.
- How do you coach CHROs and CLOs to adopt strategic technologies and keep their workforce ahead of the market?
The emergence or redefinition of jobs I just talked about, some industries are at the onset of it while some have already moved deeper into it. The need for job replacements, reskilling, and upskilling with AI technologies is an inevitable evolutionary step. The HR and learning leaders have a crucial role in making it work for the organizations, employees, and society.
However, a misconception about AI replacing jobs has spurred several organizations to ride the AI wave without much strategic planning. Also, there is another fear surrounding such a change: the workforce needs to master AI technology sooner. But the reality is that employees engaged in traditional jobs don’t have to master AI as a technology but certainly need to use AI as a tool, enabling more efficiency and automation. They need to learn how to disposition rule-based, linear, predictable tasks that require logical intelligence to an AI-based tool effectively and seamlessly.
At the same time, they need to learn how to apply deep human skills to their work processes in an ecosystem where emotional and social intelligence would be expected to co-exist with artificial intelligence. That’s where CHROs and CLOs should focus on reskilling initiatives to prepare the future workforce.
CHROs and CLOs need to be mindful that these impacts or developments are occurring at a point in time when there is a broader landscape playing its role in the background. The World Economic Forum’s 2023 Future of Jobs report predicts that employees will need more non-linear, social, emotional, and creative thinking skills by 2030 to be successful in the evolving nature of jobs.”
Regardless of the disruptive impact of technologies like AI, AR, and VR, these core human skills are still required by businesses.
Thus, forward-thinking CHROs and CLOs must develop the workforce with deep human skills and emotional and social intelligence to co-exist with AI while staying ready for future jobs. They need to act now to stay ahead of the AI curve. Harnessing the power of AI should be on each leader’s priority list.
- As a futurist and thought leader, what is your advice for leaders who are yet to make a move in building training programs that balance soft skill development with hard technical skills, especially in the context of AI as a productivity assistant?
As I mentioned, the redefinition of jobs and skills due to AI would require human-oriented skills to co-exist with the powers and potential of AI technologies. The HR and L&D leaders who are yet to make a move should start building training programs that allow well-rounded soft skill development in the context of hard technical skills, whereby employees will be taught how to leverage AI as a productivity assistant.
But I would like to mention that it is not about race to ride the AI wave. In my sessions with CHROs, CLOs, and other leaders, I observed that most of them are worried about integrating GenAI (like ChatGPT) into their organizations. Their immediate focus is how to implement it successfully in a race to stay as front runners. Next, they want to analyze the immediate repercussions of such implementation.
However, there are several daunting considerations, several of which are not answered well in the market yet before HR and L&D leaders could make a full-scale investment in AI to use as a productivity assistant.
Firstly, leaders need to be mindful that AI is still in the nascent phases with massive innovations on the horizon. They need to stay tuned to the trends and technology maturity levels. ChatGPT, Gemini, or other promising GenAI tools are just a small pie of the overall AI technology landscape.
Secondly, full-scale AI implementation requires massive investment, which involves upgrading corporate infrastructure to make it work for pre-established business processes. I believe a more reasonable approach is to pilot the add-on infrastructure onto your current corporate infrastructure without making significant changes and without taking bigger risks upfront. For instance, if your organization employs Microsoft ecosystem such as Teams, Outlook, Sharepoint, and other close-knitted platforms from Microsoft, you might be able to see the result far more quickly by piloting well-scoped AI projects in HR and L&D operations without having to struggle with technology compatibility issues.
Thirdly, you must prepare a technology induction roadmap before spearheading significant investments and infrastructure changes. A holistic view is required to understand short-term and long-term strategic goals.
And lastly, there are content copyrights, intellectual property, and information security considerations that have not been fully resolved yet.
