Polymathic

Digital transformation, higher education, innovation, technology, professional skills, management, and strategy


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    Try to make yourself obsolete

    Try to make yourself obsolete

    The idea of intentionally making oneself obsolete challenges the conventional mindset about work and job security. Instead of striving to prove irreplaceability, this approach advocates for identifying inefficiencies, eliminating redundant tasks, and questioning the necessity of one’s actions. This intentional drive for obsolescence not only sharpens personal and organizational efficiency but also fosters innovation, growth, and meaningful contributions.

    At its core, this philosophy encourages a critical reassessment of daily tasks. Are they essential? Could they be automated, streamlined, or delegated? By confronting these questions, individuals uncover a twofold benefit: eliminating unproductive work while understanding their true value within the broader context of their organization or personal endeavors.

    The Inspiration Behind Obsolescence

    The concept stems from a principle often cited in entrepreneurship: work *on* the business, not *in* it. Entrepreneurs are encouraged to design systems that allow their businesses to thrive without their constant involvement. This ensures scalability and sustainability. When applied in a non-entrepreneurial setting, the principle invites employees to adopt a similar mindset within their roles. The goal is to identify tasks that don’t require their unique skill set or could be performed more efficiently by others—or even machines.

    For example, in my career, I’ve applied this principle by evaluating tasks like writing and editing. While I may take pride in my skills, tools like large language models (LLMs) can often perform these tasks faster and with comparable quality. Recognizing this, I’ve adapted by leveraging AI to handle routine writing tasks, thereby freeing myself to focus on higher-value activities that require critical thinking or strategic insight.

    This practice doesn’t just benefit the individual; it strengthens the organization. When employees prioritize what truly matters and eliminate unnecessary work, the entire system operates more effectively.

    Identifying Redundancies and Addressing Them

    Recognizing redundant tasks requires self-awareness and a willingness to confront long-held assumptions. It’s easy to mistake busyness for productivity or to cling to certain tasks as a means of job security. Breaking free from these habits demands honesty and courage.

    In my experience, assessing redundancy involves several key questions: 

    – Can someone else do this task just as effectively?

    – Could automation handle this process?  

    – Does this task need to be done at all?  

    – Is there a more efficient way to achieve the same outcome?  

    For example, when I identified that AI tools could perform much of my routine editing work, I had to confront the emotional attachment I had to that aspect of my job. I realized that holding onto these tasks, whether out of pride or fear of change, was ultimately a disservice to my organization. By embracing automation, I enabled my team to allocate resources more effectively.

    Balancing Efficiency with Core Values

    Efficiency does not come at the expense of values; in fact, it aligns with them. Every organization should prioritize responsible resource allocation, including how employees spend their time. If a team member clings to outdated methods—such as spending hours faxing documents instead of utilizing modern communication tools—they not only squander resources but also hinder progress.

    Leaders must foster an environment of trust and shared purpose, encouraging employees to evaluate their tasks critically. For instance, I encourage subordinates to regularly ask, *What am I doing today that someone else could do, or that could be automated or eliminated?* At the same time, I challenge myself to look at my own responsibilities and ask, *What could I hand off to someone else to free up my time for more impactful work?*

    This approach creates a culture of continuous improvement, where efficiency becomes a collective value rather than an individual burden.

    Continuous Improvement: The Path Forward

    The journey toward obsolescence isn’t about avoiding irrelevance; it’s about ensuring your contributions remain meaningful. By eliminating tasks that don’t require your unique skills, you create space to take on challenges that truly matter.

    This requires two complementary practices:

    1. Regularly evaluating what tasks you can stop doing.  

    2. Proactively seeking out new opportunities that align with your skills and organizational needs.  

    For example, I’ve found success by asking superiors, *What’s on your plate that you don’t want to do anymore?* This not only lightens their load but also allows me to tackle new challenges that stretch my capabilities. Similarly, I expect my team to approach me with the same question, fostering a culture of mutual support and efficiency.

    Conclusion

    Making oneself obsolete may sound counterintuitive, but it is a powerful strategy for personal and organizational growth. By critically evaluating tasks, embracing automation, and seeking out meaningful work, individuals can ensure they remain valuable contributors while driving efficiency and innovation. This approach doesn’t diminish one’s role; it enhances it by aligning efforts with what truly matters. In doing so, we not only improve ourselves but also create a more effective and forward-thinking workplace.

  • Bookmark: 6 ways continuous learning can advance your career

    The article “6 Ways Continuous Learning Can Advance Your Career” highlights the imperative of adopting continuous learning to enhance career prospects in a rapidly evolving job landscape. The central thesis posits that ongoing skill development is crucial for maintaining career relevance and climbing the corporate ladder. The article is structured around six strategies shared by industry leaders. Dave Moyes advocates for maintaining curiosity, akin to a childlike inquisitiveness, which helps in keeping perspectives fresh and unassuming. Carrie Jordan emphasizes the importance of setting ambitious learning targets and fostering a culture of learning within her team at Microsoft. Raymond Boyle suggests choosing dynamic workplaces that naturally encourage learning through exposure to innovations and changes, specifically highlighting the data and analytics sector as a prime example. Roger Joys underscores the necessity of critical thinking to align new ideas with business value, while Phil Worsley recommends problem-solving as a way to motivate practical learning. Finally, Keith Woolley describes his job as a hobby, which naturally fosters an environment of spontaneous learning. Collectively, these insights underline the transformative impact of continuous learning, positioning it as an essential strategy for career advancement, aligned with the broader trend of skills-based hiring that prioritizes agile and adaptable mindsets.

    6 ways continuous learning can advance your career

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    Article analysis: The Future Of Corporate Learning And Employee Engagement: Why Traditional Training Is Dead

    Article analysis: The Future Of Corporate Learning And Employee Engagement: Why Traditional Training Is Dead

    A notable quote from the article is: “AI will strengthen a lot of the processes we already have established, whether it’s creation of material, analyzing reports, or understanding outcomes from different sessions.”

    The Future Of Corporate Learning And Employee Engagement: Why Traditional Training Is Dead

    Summary

    The article, “The Future Of Corporate Learning And Employee Engagement: Why Traditional Training Is Dead,” posits that traditional training methods are becoming obsolete due to the transformative impact of artificial intelligence (AI) and immersive technologies. It highlights how AI is revolutionizing corporate learning by enhancing content creation, delivery, and analysis, allowing for personalized and efficient learning experiences tailored to individual progress and preferences. The article stresses AI as a complement, not a substitute for human judgment, by leveraging great, trustworthy sources. Additionally, immersive technologies like virtual and augmented reality herald a new era of hands-on, scalable training. Despite current hardware constraints, the impact of these technologies is described as inevitable, with potential to radically improve training effectiveness. The article also addresses the evolving concept of gamification, emphasizing its role in fostering meaningful engagement and continuous learning beyond basic point systems. The hybrid work environment poses new challenges in maintaining learning consistency across remote and in-person settings, necessitating equal and inclusivity. Key future trends in corporate learning include continued integration of AI for personalized experiences, increased focus on mobile-first approaches, and heightened emphasis on engagement to drive real behavioral change and talent retention.

    Analysis

    The article adeptly highlights the transformative potential of AI and immersive technologies in reshaping corporate learning. Its emphasis on personalized learning experiences resonates with my belief in AI as an augmentation tool rather than a replacement. However, the article lacks depth in discussing the democratization of access that AI can provide, which could significantly impact underserved employees by equalizing learning opportunities. While the piece touches on AI-enhanced data-driven decision-making, it lacks a detailed exploration of how these data insights can be systematically leveraged to refine learning strategies continuously. Further, the discussion on the rise of immersive technologies lacks a critical examination of current technological and economic barriers, such as cost and accessibility issues, which may hinder widespread adoption.

    The commentary on gamification effectively notes its evolution but fails to provide empirical evidence or case studies demonstrating significant outcomes, which would strengthen claims regarding its efficacy in enhancing engagement. Additionally, the article’s treatment of hybrid work learning could benefit from more robust analysis on integrating these technologies across various sectors. Finally, while the article anticipates trends in mobile-first learning approaches, it should emphasize the critical need for continuous reskilling and adaptability in an AI-driven future, aligning with my focus on future-proofing through technology.

  • Bookmark: 41% of employers worldwide say they’ll reduce staff by 2030 due to AI

    The World Economic Forum’s bi-annual survey reveals significant expectations for AI’s impact on employment, with a dual focus on job displacement and skill augmentation. By 2030, 41% of employers predict AI will reduce their staffing levels due to automation, although a majority, 77%, plan to train staff in AI competencies, indicating AI’s dual impact on job transformation and human workforce collaboration. Covering 1,000 employers and 14 million workers across 22 industries, the report underscores a skills gap with AI, big data, networks, and cybersecurity as burgeoning areas. Creative thinking, resilience, flexibility, agility, curiosity, and lifelong learning also emerge as crucial skills. Notably, roles like graphic designers and legal secretaries are poised for decline due to AI’s growing capabilities, such as generating complex graphics easily. Despite this, the report forecasts a net job growth of 78 million jobs, driven by new job creation outpacing employment displacement, equating to a 7% growth in total employment by 2030. Employers also stress health and well-being in attracting talent, especially pertinent in the U.S. due to its unique healthcare system. The report highlights increased productivity from AI-augmented human tasks, suggesting concerns over job scarcity may be unfounded as technology enhances human productivity by performing higher-value tasks.

    41% of employers worldwide say they’ll reduce staff by 2030 due to AI

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    Article analysis: Generative AI: The Great Leadership Equalizer

    Article analysis: Generative AI: The Great Leadership Equalizer

    A noteworthy quote from the article is: “True leadership is not about who can climb the highest or accumulate the most wealth and power, but about who can guide others with wisdom, morality and an understanding of the greater good.” This statement encapsulates the central thesis of the piece, highlighting a vision for leadership that prioritizes ethical guidance over personal ambition.

    Generative AI: The Great Leadership Equalizer

    Summary

    The article “How Technology Can Drive Morality” posits that current leadership paradigms, which prioritize ambition and competitiveness, often select leaders lacking compassion and integrity. The article criticizes the existing educational and societal systems for rewarding ruthless ambition, effectively sidelining those driven by wisdom and morality. Our so-called leaders, whether political or corporate, are frequently those with a singular focus on personal triumph rather than communal benefit, resulting in pervasive corruption and a erosion of moral values. However, the article suggests an alternative: the potential of generative AI as a transformative force in leadership dynamics. Contrary to common assumptions that such technologies might diminish talent, the piece argues that generative AI could level the playing field, allowing leaders driven by humility, consideration, and integral ethics to rise without succumbing to power struggles. This technology might disrupt the Nietzschean archetype of leadership — the power-hungry “Übermensch” — and facilitate the emergence of leaders who are grounded in service, empathy, and a commitment to the greater good. The author contends that embracing AI could herald a new era of leadership, valuing decency and wisdom as much as intelligence and ambition, potentially aligning leadership with moral and ethical imperatives.

    Analysis

    From the perspective of someone deeply invested in the interplay between technology and leadership, the article presents both compelling insights and notable gaps. The central assertion that generative AI can potentially equalize the ethical and power dynamics in leadership is intriguing and aligns with my view that AI should serve as an augmentation tool rather than a replacement or mere enabler of existing hierarchies. The critique of current leadership models focused on ambition over morality is astutely observed. However, the article lacks empirical evidence to support the transformative potential of generative AI in leadership roles. The assumption that AI will naturally promote leaders who prioritize integrity remains speculative without concrete examples or data. Furthermore, the article seems to overlook the practical challenges of integrating AI into leadership processes, such as biases inherent in AI systems or the resistance from entrenched power structures that benefit from the status quo. Also, while the discussion around Nietzschean leadership models was academically enriched, it could have been substantiated by more in-depth analysis or historical case studies demonstrating such transformations. Overall, the article advocates for technology-driven moral leadership, yet it demands further investigation to credibly assert that AI can effectively recalibrate human-centric leadership qualities.

  • Bookmark: These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum

    The World Economic Forum’s Future of Jobs Report underscores a transformative shift in global employment dynamics by 2030, predicated on the expansive rise of artificial intelligence and technology. As demographic shifts, technological advancements, and economic uncertainties converge, a projected net creation of 78 million jobs stands juxtaposed with the displacement of 92 million roles. The decline of traditional clerical roles, including cashiers, bank tellers, and administrative assistants, contrasts sharply with the burgeoning demand for technology-centric positions. Roles related to AI, machine learning, fintech, and big data, alongside green and energy transition occupations, are identified as pivotal growth areas. The report, drawn from insights by over 1,000 global employers, further illuminates the shift in skill requirements, emphasizing technological prowess while valuing critical human skills such as analytical thinking, agility, and resilience. A critical observation reveals that 39% of current skills will evolve or become obsolete, signifying a gradual slowing of “skill instability” due to proactive upskilling efforts. Complementing the technological evolution narrative is the anticipated expansion of the care economy and service-oriented roles, suggesting a balanced skill ecosystem that values digital and human-centric capabilities. This landscape frames the future of work as a domain driven by continuous learning and adaptability, resonating with strategic imperatives for digital transformation and skill enhancement.

    These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum

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    Article analysis: Report: Employers Still Don’t Understand Or Trust Education Badges

    Article analysis: Report: Employers Still Don’t Understand Or Trust Education Badges

    A particularly insightful quote from the article states, “We don’t have a standard way of understanding them. People have digital credentials, but we don’t have a way to say that this credential equates to this skill, equates to this job. We need a magic decoder ring.” This quote encapsulates the core issue with digital badges: the lack of a universally understood framework for translating these credentials into tangible skills and job qualifications, underscoring the need for standardization and clarity in the digital credential landscape.

    Report: Employers Still Don’t Understand Or Trust Education Badges

    Summary

    The article “Report: Employers Still Don’t Understand Or Trust Education Badges” delves into the persistent challenges facing digital education badges, highlighting their pervasive ambiguity and lack of utility within the employment sector. Digital badges, envisioned as portable symbols of educational attainment akin to diplomas, have proliferated alongside the rise of online education, yet their unstandardized nature has resulted in confusion rather than clarity. The absence of regulation, standardization, or segmentation means badges can represent vastly different levels of learning—ranging from brief video viewing to comprehensive expert-led instruction. As evidenced by a report from UpSkill America, employers find the multitude of available digital credentials overwhelmingly indistinct, lacking a standard interpretation that hinders their practical application in hiring processes. This confusion is exacerbated by the absence of a universally accepted metric akin to degrees from recognized institutions, such as Princeton, which employers trust based on established reputations. Consequently, digital badges fail as effective communication tools, with their value questioned due to employers’ reliance on known educational providers. The article suggests that employers require clear articulation and validation of skill competence and mastery from credential holders, yet the current proliferation and ambiguity of badges impede such a distinction, limiting their role as credible career marketplace signals.

    Analysis

    The article offers a critical overview of digital education badges, highlighting issues of ambiguity and lack of standardization that are significant obstacles to their acceptance in the employment sector. However, from my conceptual commitment to AI and digital transformation, the article misses an essential narrative on how technology could resolve these issues. There is a conspicuous absence of proposals leveraging AI to create standardized frameworks for assessing digital credentials. This represents a missed opportunity to discuss how technology can drive credibility in digital learning, an area that aligns with my advocacy for tech-driven solutions.

    The article’s argument hinges on the lack of regulation, yet it fails to address how emerging technologies could optimize or automate regulatory processes, which is critical in the digital age. It predominantly rests on anecdotal evidence from selected employer interviews, which, while valuable, lack the comprehensiveness of data-driven analysis that I prioritize in evidence-based decision-making. Furthermore, the piece does not explore the potential for reskilling and lifelong learning through digital badges, a significant domain in my perspective on future-proofing the workforce. Ultimately, while the article raises important concerns, it leaves potential solutions underexplored, which could undermine its persuasive power in advocating for transformative educational approaches.

  • Bookmark: Global ad giant WPP issues sweeping RTO mandate for its 114,000 staff, calling staff back to office 4 days a week

    The article discusses WPP’s newly issued mandate requiring its 114,000 employees to return to the office four days a week. This sweeping return-to-office (RTO) policy marks a significant shift in the company’s approach to workplace flexibility following the widespread adoption of remote work practices during the COVID-19 pandemic. WPP’s CEO, Mark Read, emphasized that the initiative aims to foster creativity, collaboration, and company culture, which he believes are better facilitated through in-person interactions. While the mandate reflects a growing trend among large companies to increase office attendance, it has sparked discussions about the future of work and employee expectations in a post-pandemic world. The move is anticipated to influence industry standards around work arrangements, potentially affecting company operations and workforce dynamics. However, it raises concerns about employee morale and adaptability, particularly for those accustomed to the flexibility of remote work. The decision is emblematic of broader strategic recalibrations as companies seek a balance between operational efficiency and the evolving expectations of a tech-enabled workforce. It underscores the complex interplay between technological advancements and traditional workplace paradigms, as firms navigate the ongoing digital transformation and its implications for organizational resilience and employee engagement?4:0†Paul Welty Personal Manifesto.txt?.

    Global ad giant WPP issues sweeping RTO mandate for its 114,000 staff, calling staff back to office 4 days a week

  • Bookmark: Nvidia’s Jensen Huang says AI agents are ‘a multi-trillion-dollar opportunity’ and ‘the age of AI Agentics is here’

    Nvidia’s Jensen Huang, in his keynote at CES 2025, introduced groundbreaking advancements poised to define the next era of technology: the age of AI Agentics, emphasizing AI agents as a multi-trillion-dollar opportunity. Huang spotlighted AI’s transformative power, asserting its capacity to reshape industries through autonomous agents capable of executing complex tasks independently. He illustrated how AI agents are not merely auxiliary tools but primary components of business and industrial processes, driving unprecedented efficiency and creativity. This shift underscores Nvidia’s commitment to leveraging advanced AI as a catalyst for innovation and economic expansion, aligning with the broader push towards digital transformation. The keynote further demonstrated Nvidia’s prowess in cutting-edge hardware, unveiling the Grace Blackwell NVLink72, designed to enhance AI agent performance, thereby reinforcing Nvidia’s position as a leader in AI technology development. With these initiatives, Huang articulated a vision where AI augments human capacities, facilitating a future where technology drives deeper economic and intellectual potential. This aligns with the idea that AI not only complements human expertise but also catalyzes new, powerful synergies between human insight and machine intelligence, fundamentally changing how industries operate and innovate.

    Nvidia’s Jensen Huang says AI agents are ‘a multi-trillion-dollar opportunity’ and ‘the age of AI Agentics is here’

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    Article analysis: Not using AI is “disservice” to students 

    Article analysis: Not using AI is “disservice” to students 

    “We need to move beyond the focus on cheating and teach students to use AI in pursuit of learning not instead of learning,” added Lufkin at last week’s event.

    Not using AI is “disservice” to students 

    Summary

    The article underscores the pressing need for universities to integrate generative AI into their teaching frameworks, advocating for its role in preparing students for future workplaces and enhancing personalized learning. It portrays a strong argument made by Ryan Lufkin, vice president at Instructure, who emphasizes that avoiding AI due to privacy concerns and fears of cheating can hinder student readiness for AI-enabled jobs. This concern is underscored by a 2024 survey indicating that while 45% of students use AI, 48% feel unprepared for AI-centric work, and nearly three-quarters expect more AI literacy courses from universities. The conference spotlighted strategies for leveraging AI to individualize education and improve access, countering data showing that 36% of European institutions lack AI guidelines. Martin Bean CBE identifies challenges such as technological rapidity, policy absence, and the selection of reliable AI vendors. Examples like Fontys University’s AI feedback loop illustrate successful AI integration, while speakers like Jóhanna Bjartmarsdóttir highlight its potential in making education accessible to those with disabilities. The emphasis remains on AI as a catalyst for broadening education’s reach, encouraging institutions to view accessibility and AI as foundational in educational strategy.

    Analysis

    The article provides a compelling argument for the integration of AI in education, aligning with my belief in AI as an augmentation tool and a driver of digital transformation. The emphasis on personalized learning and accessibility resonates well with the notion of democratizing education. However, the article falls short in addressing practical strategies for overcoming resistance to AI implementation in academia, such as clear empirical evidence on AI’s tangible benefits in learning outcomes. It heavily relies on anecdotal experiences, like those of Leon van Bokhorst and Jóhanna Bjartmarsdóttir, rather than comprehensive data, which could weaken the argument’s impact on conservative educational stakeholders. Furthermore, while the challenges of vendor selection and data security are mentioned, the article lacks in-depth discussion on how institutions might navigate these complex issues effectively, which is crucial for leadership in the AI age. The criticism of European institutions for lagging behind in AI policy development could be more persuasive by incorporating a comparative analysis with institutions that have successfully implemented AI. Ultimately, the article needs to articulate more robust frameworks for AI educational integration, ensuring it aligns with future workforce needs and innovation through collaboration—a pivotal aspect of operational excellence.

About Me

Visionary leader driving digital transformation across higher education and Fortune 500 companies. Pioneered AI integration at Emory University, including GenAI and AI agents, while spearheading faculty information systems and student entrepreneurship initiatives. Led crisis management during pandemic, transitioning 200+ courses online and revitalizing continuing education through AI-driven improvements. Designed, built, and launched the Emory Center for Innovation. Combines Ph.D. in Philosophy with deep tech expertise to navigate ethical implications of emerging technologies. International experience includes DAAD fellowship in Germany. Proven track record in thought leadership, workforce development, and driving profitability in diverse sectors.

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