You in 2042 ... The Future of Work

Hosted by Danielle Wallace

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Oct 2026

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Glimpse into the future with thought provoking insights from global thought leaders. Imagine yourself in 2042 with the work world transformed around you. Get ready for this future now!

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October 15, 2026Episode 1014 min

When AI Has The Answer But Misses The Question

Bala Muthiah, a senior tech leader with a passion for community and education, explores how AI is reshaping the future of work and why human thinking will be essential to solving increasingly complex problems. He shares why the real opportunity lies not just in advancing technology, but in empowering people to ask better questions, challenge assumptions, and find solutions that AI alone may miss. Tune in to hear his perspective on inclusive innovation, curious leadership, and how bringing different human perspectives into the AI transition can help create a better future. Learn more at balamuthiah.com or connect with Bala on LinkedIn . Show Notes [00:25] Introducing Bala Muthiah Bala Muthiah shares his background in tech in the Bay Area and his involvement with nonprofits focused on community and education. He describes this as an exciting time in technology, where it feels like everything is happening at “10x speed.” [01:19] How AI Is Changing Leadership and Hiring Bala believes leaders must now be “five, ten steps ahead” as their teams become more capable with AI. He explains how hiring is shifting from traditional job descriptions toward nuanced skills, problem-solving, and people who can “think on the edges” and see things from a different lens. [03:17] From Typing Skills to Problem-Solving Using the example of typewriters, Bala explains how skills once considered specialized eventually became part of everyday work. As AI makes more tasks accessible to everyone, organizations will need people with deeper domain expertise who can identify new customer problems and solve them rather than simply follow a predefined template. [05:01] Bringing Everyone Along in the AI Transition Bala warns that technological progress can leave people behind, just as previous changes have. He shares examples of formerly incarcerated people struggling to navigate everyday technology and communities without reliable internet or electricity. He also highlights neurodivergent people whose different perspectives may be overlooked, emphasizing that bringing everyone along creates “more value for all.” [08:52] The Advantage Is in Who Uses the Tools Bala explains that AI tools are becoming increasingly capable and similar in performance, making the tools themselves less of a differentiator. What matters is “whose hands those tools are given, and what are they capable of?” He describes how neurodivergent thinkers can challenge assumptions and ask nuanced questions that AI might overlook. [11:27] Finding the Right Questions to Answer Bala believes the real differentiator is finding the right question to answer. As AI becomes better at solving problems, organizations need people who can identify overlooked challenges and ask questions that lead to meaningful solutions. [12:15] Leadership Starts With Curiosity Bala’s advice to leaders is simple: “Be curious.” With technology changing so quickly, leaders need to keep an open eye, question whether existing plans still make sense, and consider who is being brought along or left out. He believes the greatest value often lies beyond what is immediately visible. [13:16] Solving Problems That Uplift Humanity Bala encourages people to look beyond today's challenges and seek problems that will “uplift humanity.” He believes AI should not simply bring things to an end but should be used to “make everything better.” [13:53] Where to Learn More About Bala Muthiah Listeners can learn more about Bala at balamuthiah.com ⁠ and connect with him on LinkedIn ⁠ . He welcomes conversations with people who can challenge his perspective and help him think in new ways.

September 15, 2026Episode 913 min

When Efficiency Dehumanizes Work

Graham Skidmore, an entrepreneur, activist, and former C-suite executive, explores how AI can help people move beyond busy work and spend more time using the skills that make them valuable. Drawing on his own experience with burnout, he challenges organizations to rethink how people and technology work together. Tune in to hear his perspective on experiential learning, human connection, and measuring what truly matters. Connect with Graham at SAS Technologies or on LinkedIn . Show Notes [00:26] Introducing Graham Skidmore Graham shares his journey from 21 years in the corporate world, including as a C-suite executive, to reaching “the height of my success” and “the height of my misery and burnout.” After eight years of self-discovery and healing, he began his second chapter as an entrepreneur, activist, and mystic focused on “providing power to the people.” [01:47] The Strength of Experiential Learning He explains why experiential learning is one of the things that “really makes humans their strength.” Referencing the Dean Martin quote, “Good judgment comes from experience, and experience comes from poor judgment,” he explores how emotion and lived experience shape decisions and how AI can move beyond “one-size-fits-all approaches.” [03:47] Using AI to Remove the Busy Work He suggests identifying the one to three things that represent an individual or team’s real strengths, then using technology to handle the “busy work” and “distraction work.” This gives people more time to apply their subject matter expertise through problem solving, innovation, and generating revenue. [04:59] A First Principles Approach to Work He challenges organizations to stop focusing on “incremental optimization within broken systems.” Instead, he suggests taking a “first principles approach” and asking what the best-case scenario would be if they were “building this company out of our garage right now.” From there, organizations can rethink how people and technology work together. [06:39] Where Human Connection Creates Value Using customer service as an example, Graham explains how focusing on efficiency through chatbots can cause organizations to lose valuable human connection. An upset customer can become an advocate when a person turns their problem into a win. For Graham, “loyalty doesn’t come from programs and rewards and benefits” — it comes from taking care of customers. [08:29] The Dehumanization of Humans He identifies the “dehumanization of humans” as one of the worst things that can happen in the AI transition. When employees feel their ideas can simply be replaced with technology, they can become less motivated to bring forward “innovation and invention” and “free thinking,” creating a self-fulfilling prophecy of greater reliance on technology. [09:27] The 70% That Isn’t the Job Looking back on his career, Graham estimates that he spent about 30% of his time doing his job and 70% “preparing stuff for other people, dealing with other people’s stuff” and supporting work around the work. He explains how automation could free people to spend more time leveraging their subject matter expertise. [10:37] Measuring What Really Matters Graham explains why organizations need to look beyond “butts in the seat,” busyness, and traditional KPIs. Better technology and workflows can help leaders understand what it looks like when someone is truly leveraging their subject matter expertise and measure the impact that creates. [12:05] Giving Your Best People the Ability to Stand Out Graham believes that “your best people want that” when it comes to measurement. Objective measures give strong performers the ability to stand out, rather than leaving them frustrated in a subjective environment where their contributions can be harder to distinguish. [12:41] Where to Learn More About Graham Skidmore Listeners can learn more about Graham’s technology work and his manifesto for the future at SAS Technologies . He also shares articles and insights on LinkedIn .

August 14, 2026Episode 813 min

Earning a Seat at the Table in 2042

Cindy Plunkett, Senior Director of Talent Development and HR Technologies at PointClickCare , shares how AI is changing the role of L&D and what it will take for learning leaders to stay relevant in 2042. She explains why AI can take over many traditional L&D tasks, while creating an opportunity for L&D to become more strategic and closely connected to business goals. Tune in to hear her perspective on building an AI-ready workforce, proving the value of L&D, and why learning leaders need to stop being order-takers and create their own “seat at the table". Connect with Cindy on LinkedIn to continue the conversation. Show Notes 00:27] Introducing Cindy Plunkett Cindy Plunkett, Senior Director of Talent Development and HR Technologies at PointClickCare and Executive Director for the Canadian Learning Conference, brings more than a decade of experience in talent development and technology to the conversation. [01:07] Rethinking the Role of L&D in 2042 Cindy sees AI taking over many traditional L&D tasks, from creating videos and voiceovers to generating e-learning content in seconds. Rather than viewing this as a threat, she believes L&D leaders need to become more strategic—aligning their work with business goals and creating their own “seat at the table.” [01:07] Building an AI-Ready Workforce Cindy highlights the opportunity for L&D to help organizations understand and adopt AI. L&D professionals don’t need to become technical experts; they can use their expertise in talent development to identify skill gaps, build learning strategies, and partner with technical specialists. At PointClickCare, this approach helped 88% of the workforce achieve foundational AI literacy within four months. [07:33] Why Order-Takers Won’t Thrive Cindy warns that L&D professionals who simply wait for direction risk becoming redundant. As AI takes on lower-level tasks across functions, the value of human work will increasingly come from “critical thinking, problem solving, [and] strategy” and understanding where the organization needs to go next. [08:55] Proving the Value of L&D Cindy emphasizes that L&D needs to demonstrate how its work supports organizational priorities. That means going beyond basic measures like whether employees enjoyed a session and using meaningful quantitative and qualitative metrics to show business impact. [10:27] Creating Your Own Seat at the Table If L&D doesn’t have a seat at the leadership table, Cindy believes leaders can create one. By showing how initiatives align with business goals, sharing progress, measuring results, and creating regular opportunities for dialogue, L&D can build visibility and demonstrate its value across the organization. [11:03] Show Your Work Cindy explains how regular updates can keep L&D aligned with changing business priorities. Her team shares progress, measurements, and upcoming initiatives throughout the year, allowing them to adjust when priorities shift and ultimately demonstrate their impact at the board level. “It’s important to show your work,” she says. [12:41] Connect with Cindy Plunkett Cindy invites listeners to connect with her on LinkedIn to exchange ideas and connect with other learning and development professionals.

July 14, 2026Episode 723 min

AI and the Erosion of Judgement

Jelena Marjanović, an AI adoption strategist and learning expert, explores the growing risk of AI and the erosion of human judgment. Drawing on more than 15 years of experience in learning and development, she explains why relying too heavily on AI can weaken critical thinking and why organizations need to teach people to think with AI—not simply accept its answers. Tune in to hear her insights on the dangers of AI over-reliance, the difference between polished outputs and quality outcomes, and how businesses can build the judgment and decision-making skills needed to thrive in an AI-driven world. Connect with Jelena on LinkedIn or by email to continue the conversation. Show Notes [00:26] Introducing Jelena Marjanović Jelena Marjanović is an AI adoption strategist and learning expert with more than 15 years of experience in learning and development. She helps organizations implement AI in ways that improve workflows while keeping people, learning, and long-term adoption at the center of the process. [03:19] The Risk of Cognitive Decay Jelena explains why growing reliance on generative AI can gradually weaken critical thinking. While AI offers significant efficiency gains, she warns that delegating judgment to polished AI outputs without careful evaluation can lead to cognitive decay, particularly for leaders making high-stakes decisions. [05:33] Understanding the AI Over-Reliance Curve She introduces the "over-reliance curve," describing how many users move from initial excitement to over dependence before reaching a turning point. The most successful users, she explains, learn to question AI outputs and use the technology to strengthen their own thinking rather than replace it. [10:29] Why Critical Judgment Still Matters Jelena emphasizes that domain expertise alone isn't enough when working with AI. Even experienced professionals must deliberately analyze and challenge AI-generated content instead of accepting polished responses at face value. [12:15] Recognizing Quality Beyond Polished Content She discusses why effective learning requires more than well-written outputs. Without a clear understanding of what quality looks like, organizations risk producing training that appears professional but fails to improve performance or achieve business goals. [16:08] Learning and Development as a Strategic Partner Jelena argues that organizations achieve better outcomes when learning and development is treated as a strategic business function rather than simply a training provider. Embedding L&D into organizational strategy helps improve AI adoption, workforce capability, and long-term performance. [19:37] Teaching People to Think With AI She explains that successful AI adoption requires much more than learning prompts or new tools. Organizations should build competencies around judgment, delegation, quality standards, and critical thinking so employees can collaborate effectively with AI while maintaining strong decision-making skills. [22:15] Where to Connect with Jelena Marjanović Jelena shares that listeners can connect with her through LinkedIn⁠ or by ⁠email⁠ , where she regularly discusses AI adoption, workplace learning, and practical strategies for helping organizations implement AI in a thoughtful, human-centered way.

June 15, 2026Episode 613 min

Human Trust Is the New Intelligence

Ron Shah, founder and CEO of Bizly and Perch , explores why the future of work will depend as much on human connection as it does on artificial intelligence. A former venture capitalist and CNBC host, Ron shares his perspective on how AI will transform routine work while making trust, relationships, and collaboration more valuable than ever. Tune in to hear his insights on collective intelligence, the importance of meaningful networks, and why the biggest opportunities of the future may come from connecting people—not just advancing technology. Connect with Ron at Bizly , Perch , on LinkedIn , or through his Substack newsletter, Rising Sun. Show Notes [00:26] Introducing Ron Shah Ron Shah is the founder and CEO of Bisly, a platform designed to facilitate in-person connections through events, and Perch, a professional networking platform focused on building deeper relationships. A former venture capitalist and CNBC host, he now focuses on creating technology that strengthens human connection in an AI-driven world. [01:33] AI Will Replace Tasks, Not Human Challenges He predicts that AI agents will eventually handle most routine tasks, from administrative work to everyday chores. By 2042, however, the greater challenges facing society will extend beyond automation to issues such as climate change, social upheaval, and evolving government systems. [02:44] The Missing Human Layer in AI Discussing the current limitations of AI, he argues that most systems operate in isolation from the human networks that drive opportunity and collaboration. While AI can generate ideas and automate workflows, it lacks awareness of the relationships, connections, and communities that help people achieve their goals. [05:44] Unlocking Human Collective Intelligence Ron introduces the concept of collective intelligence, describing it as one of the greatest untapped opportunities of the coming decades. Rather than focusing solely on advancing machine intelligence, he believes society must find better ways to combine human knowledge, perspectives, and expertise to solve complex challenges. [07:57] Expanding Human Potential Through Connection Reflecting on the future of work, he emphasizes that humans possess far more capacity than they currently utilize. Meaningful collaboration, diverse perspectives, and shared experiences will play a critical role in unlocking greater creativity, insight, and innovation. [08:46] Creating the Conditions for Better Thinking He explores how environments, experiences, and relationships influence human performance. Whether through meaningful conversations, unique settings, or exposure to different perspectives, these human elements can help uncover insights that technology alone cannot provide. [10:17] What It Means to Be Future-Ready Acknowledging the likelihood of job displacement as AI advances, he encourages individuals to identify and clearly communicate their unique expertise. Making skills, knowledge, and accomplishments visible will become increasingly important in an AI-enabled economy. [11:11] Trust as the Currency of the Future Ron predicts that trust will become one of the most valuable assets in a world filled with synthetic content and AI-generated information. As confidence in online information declines, people will increasingly rely on trusted personal and professional relationships. [11:52] Building Deeper Networks in an AI Era He argues that success will depend less on broad networks and more on meaningful connections. Re-engaging with people we already know and trust may become one of the most effective ways to find opportunities, collaborate, and navigate uncertainty. [12:49] Where to Connect with Ron Shah Listeners can learn more through Bizly⁠ , ⁠Perch , LinkedIn⁠ , and his Substack newsletter, Rising Sun.

May 15, 2026Episode 513 min

The Hyper Adaptive Enterprise

Melissa Reeve explores why the biggest barrier to AI adoption is not technology, but outdated organizational systems. Drawing from her book Hyper Adaptive , she breaks down how legacy structures and silos limit adaptability and innovation. Tune in to hear her insights on AI-native organizations, value streams, AI activation hubs, and how companies can rewire roles, learning, and workflow for the future of work. Show Notes [00:25] Introducing Melissa Reeve Melissa’s book Hyper Adaptive: Rewiring the Enterprise to Become AI Native is available through major bookstores and online platforms. Listeners can also learn more about her work and insights at hyperadaptive.solutions and connect with her on LinkedIn. [01:24] The Legacy of Taylorism and Functional Silos She explains the “ghost of Frederick Taylor” and how Taylorism, originating in 1911, introduced the idea of management dictating the “one best way” of doing work. She reflects on how this mindset still exists in modern organizations and how it evolved through World War II-era functional specialization, which created silos such as sales, marketing, and finance. [03:33] AI Learning Systems and Activation Hubs Melissa explains the shift toward AI-native organizations, focusing on how roles, processes, and learning systems need to be rewired. She introduces the AI learning flywheel, where AI power users are supported to become change agents rather than working in isolation. She also describes AI activation hubs that track AI developments and distribute simplified insights across the organization to improve learning flow and break down silos. [07:04] Breaking Down Silos Through Networked Learning She explains that AI activation hubs can connect across departments, enabling knowledge to flow not only top-down but also across the organization. Insights from one area, such as legal, can be shared with finance or HR. She emphasizes that this creates a more deliberate learning system and addresses what she calls a “distribution problem” in how organizations share knowledge. [08:10] From Doing Work to Managing AI Systems Melissa explains that as organizations move toward automation, jobs shift from doing tasks to building, monitoring, and maintaining the systems that perform those tasks. She uses the washing machine analogy to show how technology changes the nature of work rather than eliminating it. She introduces the AI Impact Hub, which focuses on upskilling and helping employees transition into roles supporting AI-driven systems. [10:09] Defining AI-Native Organizations She defines AI-native as the ability to sense and respond in near real time. She explains that organizations will shift toward orchestrated value streams—cross-functional groups focused on delivering end-to-end customer value. Using a banking example, she shows how teams aligned to customer segments can respond faster and more effectively with AI support. [11:28] AI-Native Companies and Embedded AI She explains that AI-native companies, unlike legacy organizations shaped by Taylorism and silos, are structured around direct customer value delivery. In these organizations, AI agents are embedded into workflows, enabling more seamless and adaptive execution. [11:55] A Blueprint for Transformation Melissa explains that organizations already structured around value delivery and embedded AI agents may not need a full transformation model. However, for legacy enterprises, governments, and nonprofits, her framework provides a five-stage blueprint to gradually rewire people, processes, and roles to become more AI-native and remain competitive in a rapidly evolving landscape. [13:00] Where to Learn More About Melissa Reeve Melissa’s book Hyper Adaptive: Rewiring the Enterprise to Become AI Native is available through major bookstores and online platforms. Listeners can also learn more about her work and insights at hyperadaptive.solutions and connect with her on LinkedIn .

April 14, 2026Episode 423 min

Is Critical Thinking Overrated?

Richa Kulkarni , a secondary school student in Mississauga and DECA chapter president, shares her perspective on how work, learning, and thinking may evolve by 2042. She explores a future shaped by freelancing, remote work, and project-based careers, where individuals have more freedom and flexibility in how they design their lives and careers. Tune in to hear her thoughts on AI as an extension of human thinking, the changing role of critical thinking, and why real-world experiences—from extracurriculars to everyday interactions—may become the most important foundation for future success. Show Notes [00:26] Richa Kulkarni on the Emerging Shape of Work in 2042 Richa Kulkarni is a secondary school student in Mississauga, Ontario. She is president of her DECA chapter and also active in competitive dance, balancing academics, leadership, and extracurriculars. [01:00] Why the Traditional 9–5 Model May Fade Away She believes the 9–5 job will decline, replaced by freelancing, flexible work, and multiple income streams, giving people more control over how they work. [01:31] The Rise of Remote and Flexible Work Remote and virtual work will continue growing, allowing people to design lifestyles around their careers and choose where they live. [01:56] A Shift Toward Project-Based Careers She predicts more project-based or hourly work instead of fixed salaries, along with rising entrepreneurship, especially among children of immigrants. [04:47] Rethinking Critical Thinking Critical thinking is defined as questioning, analyzing, and interpreting information rather than accepting it at face value. Its role is evolving in an AI-driven world. [05:11] AI as an Extension of Thinking AI already supports analysis and decision-making, meaning parts of thinking may be increasingly augmented by AI tools. [05:30] Building Inclusive Learning Through AI AI and wearable tech can support different learning needs and enable more personalized education. [06:00] When Skills Become Obsolete She compares critical thinking to survival skills like fire-making, noting that as technology evolves, humans shift toward higher-level thinking. [07:57] Living in an AI-Driven World AI is compared to electricity—already deeply embedded in daily life and becoming essential infrastructure. [09:42] Reimagining Education: Ideas Over Execution Students can use AI for structure and formatting so they can focus more on ideas, reasoning, and deeper thinking. [10:48] Why AI May Not Be Making Us Lazy Richa argues AI does not reduce effort, as generating ideas requires more cognitive work than mechanical execution. [11:45] The Boundaries of Machine Creativity AI accelerates existing thinking but does not create truly new ideas. Human imagination and lived experience remain essential. [15:53] Short-Form Content and Initiative Short-form content is shaping attention spans and reducing initiative among young people. [16:40] Initiative as a Key Skill Success depends on initiative—actively seeking opportunities and taking ownership of growth. [17:30] The Growing Gap in Outcomes A widening gap is forming between highly driven individuals and those who disengage. [18:08] The Real Issue The issue is not intelligence, but lack of real-world engagement and experience. [18:34] Why Real-World Experience Matters Clubs, work, and social interaction are key for developing creativity and problem-solving skills. [19:58] Declining Offline Engagement Reduced real-world engagement may weaken skill development and idea generation. [20:21] Where Creativity Comes From Creativity comes from boredom, silence, and real-world exposure. [21:51] Extracurriculars as Training Ground DECA, co-op, and sports build real-world skills through practice and interaction, not theory alone. [23:14] Experience as the True Foundation Future readiness depends less on critical thinking alone and more on lived experience shaping how people think and act.

March 14, 2026Episode 316 min

Don’t Surrender Your Thinking

John Bennett, a lifelong entrepreneur with more than 37 years of experience, shares his perspective on how AI is reshaping the way we think and work. Having witnessed multiple waves of technological change—from e-commerce and social media to today’s AI revolution—he now focuses on helping people cut through the noise and understand how to use AI thoughtfully. Tune in to hear his insights on productive skepticism, the risk of losing critical thinking skills, and why AI should be treated as a tool—not a substitute for human judgment. Connect with John at formidably.com or explore his book Don’t Surrender Your Thinking , available through major online booksellers. Show Notes [00:26] Introducing John Bennett John Bennett is an entrepreneur with more than 37 years of experience. His journey began selling cans of Coke to classmates at school and has spanned decades of technological change—from the rise of e-commerce and social media to today’s AI revolution. Today, he focuses on helping people understand AI and cut through the noise surrounding it. [01:30] How AI Could Change Judgment at Work John believes the biggest shift AI will bring is not just automation but how people respond to it. If we “mindlessly accept what AI gives us,” we risk losing our ability to think, decide, and apply judgment. But when used critically, AI can save time and strengthen human thinking. [03:23] The Rise of “Productive Skepticism” John says critical thinking will become both more valuable and less common. He describes the skill needed in the future as productive skepticism—being open to AI outputs while still evaluating them carefully. [04:04] The Risk of Thinking Skill Atrophy John compares today’s reliance on AI to how GPS replaced map-reading skills. In the past, people mentally planned routes; today, most rely on automated directions. The same risk exists for decision-making and critical thinking if we rely too heavily on AI. [05:06] Start with Human Intent John recommends approaching AI with clear intent. Instead of treating AI responses as answers, they should be seen as drafts—refined through human expertise, judgment, and accountability. [06:22] Rebalancing AI with Human Interaction Alongside learning to work with AI, John emphasizes the importance of human connection. Conversations with colleagues, communities, and peers help validate ideas and keep work grounded in human perspective. [07:31] AI as an Amplifier John describes AI as an amplifier. If we approach work thoughtfully and critically, AI can strengthen those abilities. But if we seek shortcuts or minimal effort, AI will amplify that as well. [09:22] Choosing the Level of Thinking Working with AI requires deciding how much thinking and intervention to apply each time. Sometimes, a minimal review is enough, but the key is making a conscious choice rather than accepting outputs blindly. [11:58] Understanding What AI Really Is John explains that generative AI models are essentially pattern-prediction machines . They generate responses based on probabilities from vast datasets—they don’t truly understand the world the way humans do. [14:00] Strengthening Critical Thinking Skills The good news is that critical thinking grows through use. Curiosity, questioning assumptions, and maintaining a growth mindset help build stronger thinking over time. [15:41] Where to Learn More from John Bennett John’s book Don’t Surrender Your Thinking is available through major online booksellers. Listeners can also learn more about his work at formidably.com ⁠ .

February 15, 2026Episode 213 min

Beyond Automation: Human Skills in Action

Lorne Novolker, co-founded Prospero Learning and a seasoned leader in talent development and digital transformation, shares how organizations can navigate workforce change in an AI-accelerated world. From putting strategy before software to integrating AI into core talent decisions, he explains why this moment requires thoughtful leadership—not fear-driven reactions. Tune in to hear his perspective on human differentiators like empathy and judgment, the shift from task-based work to decision-based roles, and the critical debate between skills-first and AI-first strategies. Connect with Lorne at novolker.com or on LinkedIn . Show Notes [00:01] Introduction to Lorne Novolker Lorne Novolker is a seasoned leader in learning, talent development, and digital transformation. He co-founded Prospero Learning and was a former executive at GP Strategies and Calian Learning. He now advises organizations on AI-driven talent strategy and EdTech innovation, helping leaders navigate workforce transformation in an AI-accelerated world. [02:02] AI and the Crossroads of Talent Strategy He describes this moment as both exciting and unsettling, emphasizing that AI must move beyond IT and into core talent strategy. Organizations need to rethink how they recruit, develop, and lead in a way that integrates AI without creating fear. [03:43] Strategy Before Software Lorne stresses that AI implementation requires strategic thinking—not just software deployment. The real opportunity lies in integrating AI with human capability, not treating it as a standalone technical solution. [05:07] Lessons from Past Digital Transformations Drawing parallels to the fax machine, email, and social media, he reflects on how each wave of technology reshaped work. These past evolutions offer important lessons for how we approach AI’s rapid acceleration today. [05:50] Human Differentiators as Premium Skills He emphasizes that empathy, critical thinking, context, and judgment will become even more valuable. Rather than competing with AI, humans must complement it by focusing on uniquely human strengths. [07:33] From Task-Based Work to Decision-Based Roles Lorne explains that work is shifting away from repetitive tasks toward decision-making and critical thinking. Judgment, in particular, becomes a defining capability in the AI-enabled workplace. [08:50] Learning Faster Than the Pace of Disruption With AI accelerating change, he underscores that thriving will depend on the ability to learn faster than disruption unfolds. [09:36] The Cost-Cutting Trap He identifies a major pitfall: organizations focusing primarily on cost savings rather than long-term value creation. This mindset fuels workforce fear instead of innovation. [11:30] The Skills-First or AI-First Debate Lorne outlines the strategic dilemma many organizations face: Should they build a strong skills architecture first and layer AI on top? Deploy AI rapidly and adapt skills later? Or attempt both in parallel? The approach taken will significantly shape future outcomes. [13:04] Connect with Lorne Novolker He invites listeners to connect via LinkedIn ⁠ or visit ⁠ novolker.com to continue exploring how AI and talent strategy can evolve responsibly and effectively.

January 14, 2026Episode 17 min

Beyond the Degree: Future-Proofing Students for 2042

Emily Coleman, Co-Founder and CEO of a higher education data analytics company, shares how colleges can prepare students for the jobs of 2042. She explains how predictive modeling informs enrollment, retention, and student success, why adaptability is critical in higher education, and how alternative degree models and data literacy can future-proof graduates. Learn practical insights on using data, nimble strategies, and innovative learning models to help students—and institutions—thrive. Connect with Emily at haianalytics.com or on LinkedIn @EmilyColeman . Show Notes [00:26] Introducing Emily Coleman Emily Coleman is the Co-Founder and CEO of a data analytics company serving higher education. With over 23 years in the field, she and her team build predictive models for “admit-to-enroll yields, retention, and student success,” helping institutions make more informed decisions. [01:04] Preparing Students for 2042 Jobs Emily notes that while data science and AI programs are important, the larger issue for colleges and universities is adaptability. She explains that higher education struggles to “shift strategy around to meet new needs” due to its structure—tenured faculty, physical campuses, and long-standing systems. Institutions that learn how to be more nimble, she says, will be the ones that succeed. [02:18] Why Data-Driven Decision Making Matters Emily reflects on how far higher education has come, explaining that when she started her career, a data-driven strategy wasn’t widely embraced. Today, “almost every job has some sort of data component,” even if individuals aren’t directly working with the data themselves. [03:37] Predictive Modeling in Higher Education She describes how universities rely on predictive modeling to support enrollment goals that go beyond headcount and revenue. Schools use data to balance program needs, geographic and ethnic diversity, and limited financial aid—while also examining retention and student satisfaction. Data, she says, now works alongside experience and intuition to confirm or challenge assumptions. [03:54] Data Literacy and Job Readiness Emily explains that most students now graduate with some exposure to data or statistics. While not every career requires great technical skills, she believes understanding how data informs decisions helps graduates be “better off” in a workforce where data is used across industries. [05:03] Rethinking the Traditional Degree Model As more students question the value of a four-year residential degree, Emily emphasizes the need for alternative learning models. She points out that “everyone coming for four years” is no longer practical, especially for working adults, parents, and non-traditional students. Institutions that meet learners where they are will be more sustainable long-term. [06:34] Accelerated Degrees and Return on Investment Emily highlights the growing use of accelerated degree programs, noting that saving even a year of tuition can make a significant difference—while still keeping job outcomes and future-ready skills in focus. [09:07] Where to Learn More Emily invites listeners to connect with her on LinkedIn or visit her company’s website at haianalytics.com to learn more about her work in higher education and data analytics.