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AI-Driven Continuous Learning in Leadership


Person with books in digital art style for education day
Person with books in digital art style for education day

Introduction

Rapid technological advances create a pressing need for organisations to continually upskill talent. Yet only 10% make learning a priority. Why this gap when 87% of employees say professional growth opportunities strongly influence job satisfaction?


Barriers like limited budgets, unclear skill strategies and ineffective methods impede learning. But for digitally-driven firms, AI presents a timely solution - automating everything from quarterly assessments to personalised recommendations at scale.


This post explores how Chief Information Officers (CIOs) can spearhead continuous learning innovations. As overseers of expanding AI systems, CIOs are ideally positioned to integrate them into capability building. We’ll uncover leading strategies and examples of revolutionising workplace education through automation.


The Competitive Imperative for Continuous Learning

As AI, automation and digitisation reshape industries, in-demand skills are evolving faster. The World Economic Forum predicts that over half of employees will require reskilling by 2025 as emerging roles outweigh declining ones.


Lifelong learning is now essential for both individual and organisational resilience. Firms that support regular upskilling experience:


  • Innovation – Developing novel products, services, and processes builds a competitive advantage

  • Engagement – 87% of millennials rate learning opportunities as top workplace motivators

  • Retention – Reskilling initiatives make employees feel invested in and boost tenure

  • Productivity – Fresh skills and motivated teams directly impact the bottom line


Despite the clear need, only 10% of L&D leaders make learning a top priority today. Just 10-20% of workers participate in training yearly.


This lagging investment risks strategic human capital loss. But how can resource-strapped learning teams meet surging demand? AI-powered continuous learning systems can multiply impact.


The Promise of AI-Driven Learning

Applying automation to curate personalised education at scale, AI learning platforms:


  • Profile skills/goals – Algorithms assess individual strengths and gaps via surveys, performance data and résumés/CVs.

  • Prescribes training – Based on role needs and aspirations, intelligent systems recommend targeted learning.

  • Provides flexible access – Learners consume frictionless education anytime on smartphones and devices through app-based formats, including podcasts, videos, articles and quizzes.

  • Measures efficacy – Systems gauge progress through proficiency assessments and tune recommendations accordingly in a feedback loop.

  • Optimises programs – AI refines learning strategies to maximise engagement and performance by analysing usage patterns.


This AI-human partnership achieves exponential reach. And as learning becomes intrinsically rewarding through personalisation, participation grows organically without mandates.


Leading examples like Volley, EdApp, and 360Learning demonstrate that adoption doubles yearly. By incorporating AI, CIOs can make continuous skilling a scalable priority.


Strategies for CIOs to Champion AI Learning

As overseers of emerging technologies, CIOs possess ideal awareness, authority and cross-function visibility to pioneer AI learning.


Here are five high-impact areas to demonstrate leadership:


1. Sponsor Use Cases Showcasing AI Value

AI-enhanced learning still carries scepticism. CIOs can fund small prototypes targeting key pain points like productivity lags or role churn to prove ROI. Measurable successes endorsed by tech heads legitimate expansion.


2. Promote Platform Literacy Through Immersion

Unfamiliar systems spur resistance. CIO participation in platform trials builds firsthand experience while setting adoption examples. Require team testing for a set period, then facilitate reflective knowledge sharing on user experience.


3. Establish Feedback Channels with L&D and Lines of Business

Regular touchpoints, focus groups, and training for non-tech colleagues foster understanding of AI learning capacities. CIOs can address concerns, convey system strengths, and gather requests to guide vendor selection/configuration for role needs.


4. Govern Data Integration and Security

Employees using third-party learning apps share significant personal information. CIO oversight ensures regulatory compliance, access controls and responsible data usage while conveying an organisational commitment to ethical AI principles.


5. Scale AI Learning Through Department Budgets and Policies

Once trial efficacy convinces sceptical groups of AI’s advantages, CIOs can fund access through tech budgets. Gradually institute team usage requirements and then enforce adoption while analytics diagnose successes and areas for system refinement.


Reimagining Workplace Learning With AI

Rather than struggling with limited L&D capacity, organisations can reinvent skill-building by applying AI's personalised touch. However, embracing AI in learning and development (L&D) has challenges. Misinterpretations of material, outdated information due to rapidly evolving markets, and the lack of rich, face-to-face interactions that facilitate deeper understanding and perspective sharing are notable concerns. These risks necessitate a balanced approach, combining AI's efficiency with human-led discussions to enrich learning experiences.


As digital stewards directing capability advancement, forward-thinking CIOs are positioned to sponsor this transformation. They play a pivotal role in funding pilots, scaling usage, and ensuring that AI-enabled learning platforms are continuously updated and complemented by human interaction. Through hands-on engagement, CIOs can inject momentum into a continuous learning culture critical for preparing workers to outpace unrelenting change while mitigating the risks associated with AI training.


The competitive stakes are undeniable - securing highly skilled talent has never been more vital amid ongoing disruption. When thoughtfully implemented, AI-enabled learning helps secure the human capital needed to remain relevant and resilient. Nevertheless, integrating AI in L&D requires careful consideration of its limitations and a strategic blend of technological and traditional learning methods. The time for CIOs to activate the promise of continuous reskilling through AI, with an eye on these challenges, is now.


About the Author

Giles Lindsay is a technology executive, business agility coach, and CEO of Agile Delta Consulting Limited. Giles has a track record in driving digital transformation and technological leadership. He has adeptly scaled high-performing delivery teams across various industries, from nimble startups to leading enterprises. His roles, from CTO or CIO to visionary change agent, have always centred on defining overarching technology strategies and aligning them with organisational objectives.


Giles is a Fellow of the Chartered Management Institute (FCMI), the BCS, The Chartered Institute for IT (FBCS), and The Institution of Analysts & Programmers (FIAP). His leadership across the UK and global technology companies has consistently fostered innovation, growth, and adept stakeholder management. With a unique ability to demystify intricate technical concepts, he’s enabled better ways of working across organisations.


Giles’ commitment extends to the literary realm with his forthcoming book: “Clearly Agile: A Leadership Guide to Business Agility”. This comprehensive guide focuses on embracing Agile principles to effect transformative change in organisations. An ardent advocate for continuous improvement and innovation, Giles is unwaveringly dedicated to creating a business world that prioritises value, inclusivity, and societal advancement.


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