『The Use Case Podcast』のカバーアート

The Use Case Podcast

The Use Case Podcast

著者： WRKdefined
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Discover insights from tech leaders on The Use Case Podcast. Learn how they make compelling business cases for their technology. Get inspired to enhance your business with innovative ideas. Proudly brought to you by WRKdefined with hosts William Tincup and Ryan Leary.All rights reserved by WRKdefined マネジメント・リーダーシップ リーダーシップ 経済学
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  • Everybody’s Talking About Skills. Almost Nobody Can Prove Them

    Everybody’s Talking About Skills. Almost Nobody Can Prove Them
    2026/06/10
    Most companies still confuse content consumption with actual learning. Watch the video. Pass the quiz. Move on. Todd Moran explains why that model is collapsing fast, especially now that AI is changing jobs faster than companies can retrain people. The real shift isn’t “learning content.” It’s continuous skill development tied to feedback, practice, mentoring, and real proof of capability. AI, workforce development, upskilling, learning science, coaching, talent experience. This conversation gets into where enterprise learning is finally headed. In this episode, Todd Moran breaks down why traditional LMS systems are failing modern workforces, why skill decay is becoming a major business problem, and why companies need continuous learning instead of one-time training events. Sharp conversation on AI, mentoring, coaching, workforce agility, learning science, and proving employees actually learned something. Key Takeaways : “Content does not equal learning” was one of the strongest themes of the conversation Most enterprise learning systems still measure completion rates instead of real capability Todd says skill development should include practice, feedback, coaching, and peer interaction NovoEd works with enterprise organizations with 25,000+ employees globally One hospitality client manages learning across a workforce of 800,000 distributed employees Traditional “one-time training intervention” models are failing modern organizations Todd argues companies must revisit workforce skilling continuously, not annually One airline client retrains 50,000 airport service employees every quarter using micro-learning experiences Employees respond positively when companies visibly invest in their development repeatedly AI-generated content is forcing learning platforms to focus more on proof of skill mastery “Skill decay” is becoming a major issue as jobs and technologies evolve faster Todd believes learning, mentoring, coaching, and talent development are converging into one ecosystem Companies are demanding evidence-based learning instead of self-reported progress NovoEd built video practice environments where employees can rehearse skills safely and receive peer feedback Todd says responsible AI deployment matters more than shipping features quickly Guest : Todd Moran Chief Learning Strategist at NovoEd, helping enterprises rethink workforce development through collaborative learning, mentoring, coaching, and continuous skill-building at scale. LinkedIn: https://www.linkedin.com/in/toddhmoran Website: https://novoed.com/ Connect with Us : William Tincup, LinkedIn: https://www.linkedin.com/in/tincup/ Ryan Leary, LinkedIn: https://www.linkedin.com/in/ryanleary/ WRKdefined : Website: http://www.wrkdefined.com TikTok: https://www.tiktok.com/@wrkdefined LinkedIn: https://www.linkedin.com/company/wrkdefined Facebook: https://www.facebook.com/WRKdefined/ Twitter (X): https://twitter.com/WRKdefined Substack: https://wrkdefined.substack.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices
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    43 分
  • The Resume Is Dead | Show Me You Can Actually Do the Job

    The Resume Is Dead | Show Me You Can Actually Do the Job
    2026/06/02
    One polished resume used to get you noticed. Now AI can generate hundreds of them in minutes. Ellie Angell explains why hiring teams are losing trust in traditional applications and why job simulations are becoming one of the fastest-growing ways to identify real talent. The hiring process is shifting from claims to proof. Skills assessments, job simulations, AI hiring, candidate experience, talent evaluation. This conversation explores what happens when recruiters stop asking candidates what they can do and start watching them do it. In this episode… Ellie breaks down why resumes are becoming less reliable, how realistic job simulations uncover hidden talent, and why hiring teams are moving toward skills-based evaluation. Sharp discussion on AI-generated resumes, candidate screening, assessment design, hiring accuracy, and the future of talent acquisition. Key Takeaways : • Ellie says AI has fundamentally weakened recruiter trust in resumes because candidates can now optimize applications instantly • Many employers receive 100+ applications per role, making it impossible to evaluate everyone manually • Recruiters reportedly spend only a few seconds reviewing many resumes before making an initial decision • Skills assessments help uncover qualified candidates who may be overlooked because of weak resumes or unconventional backgrounds • Job simulations allow candidates to demonstrate real capabilities instead of simply describing them • Companies are increasingly hiring for potential, adaptability, critical thinking, and attention to detail • Ellie believes future hiring will rely less on credentials and more on proof of skills • Candidate assessments can act as realistic job previews, helping applicants decide if they actually want the role • Some companies design simulations as “a day in the life” experience to show candidates what the work really looks like • The best assessments test the hardest parts of the job, not the easiest ones • Retention improves when candidates understand the realities of the role before accepting an offer • Hiring teams are increasingly evaluating how candidates use AI, not whether they use AI • Employers want to see prompting ability, judgment, and decision-making alongside technical skills • AI-assisted scoring can help standardize candidate evaluation and reduce inconsistencies in the hiring process • The strongest hiring systems combine human judgment with structured skills validation rather than relying on resumes alone Guest : Ellie Angell Head of Customer Success at Canditech, helping organizations replace resume-driven hiring with skills assessments, job simulations, and data-backed candidate evaluation. LinkedIN : https://il.linkedin.com/in/ellieangell Connect with Us : William Tincup LinkedIn: https://www.linkedin.com/in/tincup/ Ryan Leary LinkedIn: https://www.linkedin.com/in/ryanleary/ WRKdefined : Site: http://www.wrkdefined.com TikTok: https://www.tiktok.com/@wrkdefined LinkedIn: https://www.linkedin.com/company/wrkdefined Facebook: https://www.facebook.com/WRKdefined/ Twitter (X): https://twitter.com/WRKdefined Substack: https://wrkdefined.substack.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices
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    35 分
  • Billion-Dollar Software Still Fails If Nobody Uses It

    Billion-Dollar Software Still Fails If Nobody Uses It
    2026/05/19
    45% of internal workflows are still humans chasing humans. IT tickets. HR requests. Procurement approvals. Slack pings. Endless handoffs. This episode gets into why most enterprise automation failed, why forms are dying, and why Agentic AI is finally changing the game. AI workers. Workflow automation. Digital adoption. Employee experience. Enterprise AI. In this episode… Maor Ezer breaks down how AI workers are replacing rigid workflows with systems that learn, adapt, and execute like humans. They talk ROI, employee trust, autonomous agents, AI adoption, and why speed is becoming the real competitive advantage inside enterprise companies. Key Takeaways : • 45% of internal workflows are still human-to-human service requests • Most enterprise automation failed because it was too rigid and broke whenever systems changed • AI workers can already resolve 30% of IT tickets inside enterprise environments • One AI worker moved from the 10th-best “employee” to #1 in workload handled within 30 days • The old automation model was “if this then that.” Agentic AI works more like a human making decisions • Employees don’t want more forms. They want to type messy requests naturally in Slack or chat • Companies are starting to compare AI budgets directly against labor budgets • AI adoption spikes when employees see the tech making them faster, not replacing them • Practitioners doing the actual work usually know the best automation opportunities • The companies winning with AI have leadership and employees aligned on transformation • Revenue-per-employee is becoming a major metric for investors and operators • The next phase of AI is action, not recommendation. The value is in execution, not answers Connect with Us : William Tincup LinkedIn: https://www.linkedin.com/in/tincup/ Ryan Leary LinkedIn: https://www.linkedin.com/in/ryanleary/ WRKdefined : Site: http://www.wrkdefined.com TikTok: https://www.tiktok.com/@wrkdefined LinkedIn: https://www.linkedin.com/company/wrkdefined Facebook: https://www.facebook.com/WRKdefined/ Twitter (X): https://twitter.com/WRKdefined Substack: https://wrkdefined.substack.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices
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    36 分
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