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Dean Batson, a communications instructor at Arizona State University (ASU), thought he had designed the perfect midterm exam for his <a href="https://successcom.wpenginepowered.com/the-art-of-persuasion-4-tips-to-master-influence/">persuasion</a> class. He asked his students to analyze publicly available marketing campaigns using the persuasion principles they had learned in class and turn in a written report. What could go wrong?



Turns out, everything. Almost all 31 students submitted papers on one of two companies: Dove soap and Coca-Cola. A quick investigation revealed those two companies were the go-to responses when ChatGPT received a prompt on the assignment.&nbsp;







"Right off the bat, I knew they were using AI to some extent," says Batson. "Some of them had opening paragraphs [that were] identical. [I said] to myself… ‘This isn't going to work. I need to change it.’"



Batson's experience is not unique. The same phenomenon is unfolding across campuses worldwide. The rise of consumer AI, such as<a href="https://chatgpt.com" target="_blank" rel="noreferrer noopener"> ChatGPT</a>,<a href="https://claude.ai" target="_blank" rel="noreferrer noopener"> Claude</a> and<a href="https://gemini.google.com/" target="_blank" rel="noreferrer noopener"> Google's Gemini</a>, has shattered the educational paradigms most of us grew up with, forcing educators to face the uncomfortable truth that traditional education was coasting on life support until the tech companies unceremoniously pulled the plug.



We're in an age where <a href="https://successcom.wpenginepowered.com/want-to-reach-your-potential-then-be-a-learner/">learning</a> can be outsourced, and academic integrity is often an afterthought. Long term, we'll start to see professionals, such as doctors, lawyers, accountants and engineers, who lack a fundamental mastery of their specialization.



To combat this slide toward AI dependence, forward-thinking educators have adopted three key transformations: reimagining assessment methods that prioritize uniquely human skills, developing educational frameworks that teach students to collaborate with AI rather than relying on it and creating new ways to measure learning.



<h2 class="wp-block-heading" id="h-transformation-1-changing-the-assessment-methods-nbsp">Transformation 1: Changing the assessment methods&nbsp;</h2>



Traditional methods of assessing knowledge, such as written tests, quizzes and term papers, were easy and efficient to handle many students at once. However, educators observed that these assessment methods are untenable in a world where AI can easily generate these outputs.



Adnan Rasool, Ph.D., director at the Center for Teaching and Learning at the University of Tennessee at Martin, notes that rather than giving students a final paper that accounts for 35% of their final grade, he has implemented regular individual presentations throughout the semester, which account for 25% of a student's final grade.



The shift forces students to demonstrate a fundamental understanding by thinking on their feet, defending their arguments and responding to cross-examination in real time. Even if students use AI to prepare for oral examinations, AI cannot advocate on their behalf in front of their peers. Rasool also noted that he and many of his colleagues have started using in-class handwritten exams featuring fewer, more comprehensive questions.



Ironically, AI's disruption pushed educational assessment back to pre-internet era forms of evaluation, proving that sometimes the best way forward is to remember what worked before technology complicated everything.



<h2 class="wp-block-heading" id="h-transformation-2-promoting-human-ai-partnership-not-dependence">Transformation 2: Promoting human-AI partnership, not dependence</h2>



For some educators, the deep integration of AI into daily life makes bans counterproductive. Instead, some educators are teaching students to collaborate with AI ethically.



MacKenzie Price launched Alpha School based on the premise that children born in the last 20 years are digital natives, and, as such, their education needs to be completely reimagined for an AI-augmented world. Her school relies on AI tutors who teach academic subjects for just two hours each morning, while the remaining hours of the day are spent learning prompt engineering (how to communicate with AI) and developing human skills such as critical thinking, creativity, collaboration and communication.



Price's school deliberately avoids chatbot interfaces that enable cheating. "We do not use a chatbot feature… because often students use chatbots to cheat," she notes. "Instead, [we use AI] to provide personalized learning plans that meet every student [at their exact] level." This system ensures that students see AI as a tool rather than a shortcut. The result is AI-literate students who can partner with AI ethically while mastering uniquely human skills AI cannot replicate.



On the institutional side, Zhuoer (Joy) Chen, who works with educators at AI platform HeyGen, emphasizes that effective AI integration requires significant investment in comprehensive teacher training. She notes that educators who don't understand AI themselves cannot effectively guide students in using these technologies to achieve better learning outcomes.



<h2 class="wp-block-heading" id="h-transformation-3-find-new-ways-of-measuring-learning">Transformation 3: Find new ways of measuring learning</h2>



"The best AI work is C-grade," says Rasool. "One of the things [we're doing] is instead of burning through our time trying to accuse people of cheating and then spending time trying to prove that… cheating happened or not… we're encouraging folks to grade AI work as what it is.



"If you think this is not a C and you think this is not the grade you deserve, explain in detail how this is not a C. And 99. 9 % of the time, nobody's going to show up to tell you how this is not a C.”



Setting a baseline expectation of AI-generated work helps create natural consequences that distinguish genuine learners who excel by incorporating original thinking into their work from students who see their grades plateau at mediocre levels due to their over-reliance on AI.



Price's Alpha School exemplifies comprehensive new measurements through mastery-based learning where students must reach 90% proficiency before advancing to the next academic milestone, with AI tutors tracking knowledge gaps in real-time. The school validates progress through third-party Measures of Academic Progress (MAP) assessments, which are administered three times a year.



In this new AI-powered environment where limitless knowledge is readily available and the capabilities of large language models expand exponentially, the professional landscape is shifting dramatically. Future doctors and lawyers might no longer require encyclopedic knowledge of their fields, and the new methods for determining professional competence remain an open question.



What is certain is that this challenge requires more than just simple academic reform. The educators pioneering these changes might not know precisely what the future holds. However, they're ensuring their students develop the adaptability and human-centered skills needed to thrive in whatever comes next.



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Discover how ChatGPT has changed the world of education and how teachers ensure their students still acquire human skills in the age of AI.

Dean Batson, a communications instructor at Arizona State University (ASU), thought he had designed the perfect midterm exam for his persuasion class. He | SUCCESS

Reimagining Education for Gen Z in the Age of AI 

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Reimagining Education for Gen Z in the Age of AI | SUCCESS

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Chi Odogwu

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When ChatGPT launched in late 2022, I instinctively knew that the era of traditional knowledge work would soon be over. It was only a matter of time.&nbsp;Rather than resist the inevitable change, I chose to lean into it and pivoted into AI education and consulting in spring 2023. I started teaching young students on <a href="https://outschool.com/" target="_blank" rel="noreferrer noopener">Outschool</a> how to master ChatGPT and other generative artificial intelligence (AI) tools like Midjourney before expanding my training and <a href="https://successcom.wpenginepowered.com/business-to-consider-consulting/">consulting</a> to small and mid-sized businesses.







However, I wasn't ready for how quickly and unevenly AI's impact would reshape the business landscape. Within months, “AI” had become the trendiest buzzword, with organizations of all sizes scrambling to figure out their AI strategy based on the visions of soaring <a href="https://successcom.wpenginepowered.com/8-things-killing-your-productivity/">productivity</a>, lower costs and sky-high profits sold to senior executives in boardrooms across America and around the world by consulting mega-corporations. But today, some businesses investing in their AI transformation have yet to achieve their desired goals despite the large sums of money spent.



As Sara Davison, the co-founder of AI BuildLab, observes, "A lot of the hype around the race to adopt the technology was probably going a lot faster than the maturity of the people understanding how to leverage this technology the best." This is the AI productivity paradox at work. Massive hype and massive investment chasing a trend that yields minimal tangible ROI for some companies. A 2024 research report by <a href="https://www.upwork.com/research/ai-enhanced-work-models" target="_blank" rel="noreferrer noopener">The Upwork Research Institute</a> found that 77% of employees say AI tools have decreased their productivity and increased their workload.



In this article, I'll share how organizations can overcome this paradox. We'll explore practical, human-centered strategies like human-AI collaboration skills, targeted middle-management engagement and workforce development that produce measurable outcomes rather than simply adopting the latest flashy technologies.



<h2 class="wp-block-heading" id="h-focus-on-human-ai-collaboration-skills">Focus on human-AI collaboration skills</h2>



One of the most effective approaches to implementing AI in an organization is redesigning workflows around the complementary strengths of humans and AI rather than attempting wholesale <a href="https://successcom.wpenginepowered.com/klarna-pauses-hiring-in-favor-of-ai/">replacement of workers</a>. There's the misconception that AI can replace entire job functions overnight. That may be possible in the not-too-distant future, but powerful tools like ChatGPT and other popular consumer and enterprise AI need human collaborators and architects working behind the scenes to direct, refine and verify their output to ensure consistent quality over time.



"One of the big problems is not clearly defining what implementing at scale means. What does success look like when you unlock a bunch of licenses for your team? If you buy a thousand licenses for your organization, that's not implementing AI. That's purchasing a tool…. " says Josh Huston, AI consultant and founder of Quick AI Wins. "What most people need is to learn how tools like ChatGPT and Copilot can help them in their day-to-day, which doesn't include programming anything. It includes them opening the app, knowing what the features in that app can do for them, and knowing what they can ask that app to do."



An excellent example of human-AI collaboration in action is the <a href="https://radiology.ucsf.edu/blog/breast-cancer-risk-could-be-determined-seconds-artificial-intelligence" target="_blank" rel="noreferrer noopener">University of California, San Francisco (UCSF) Mirai AI System</a>. According to UCSF, the AI helps radiologists provide personalized risk assessments by analyzing mammograms to predict breast cancer risk in seconds. The system can detect subtle tissue patterns that may not be discernible to the human eye. Researchers at UCSF report that this enables timely interventions like additional screenings for high-risk patients, potentially detecting cancers that might be missed by traditional screening guidelines. Redesigning a doctor’s workflow to include this technology and others like it leverages the strengths of both humans and machines rather than simply adding AI to existing processes.



<h2 class="wp-block-heading" id="h-leverage-middle-management-as-ai-champions">Leverage middle management as AI champions</h2>



One of the biggest reasons companies fail to achieve significant productivity gains from AI is that many senior leaders do not fully understand its capabilities and limitations. Rather than a simple divide where AI excels only at routine tasks and struggles with all complex work, the reality is more nuanced. The most successful implementations match AI to the right types of complexity. For example, AI code editors like Cursor, in collaboration with Claude, can migrate entire codebases from one framework to another in hours instead of weeks, even handling complex technical implementations. However, these same systems may struggle when faced with novel problems requiring creative problem-solving or dealing with ambiguous requirements where human judgment and contextual understanding of a business are critical.



When asked about the common obstacles that affect the full-scale implementation of AI in an organization, Tyler Fisk, also a co-founder of AI BuildLab, notes that "it comes back to training and usage because ultimately, we can build out a really good system, but if the people who are going to be using the system aren't necessarily well trained or even if they've gone through the training and it's not really resonating or it's not landing with them, that's going to cause problems."



This underscores the vital role of middle management in successful AI adoption. Middle managers who embrace AI rather than see it as a threat are valuable to their organizations because they can identify valuable implementation opportunities while mitigating risks. They serve as a bridge between technical teams and leadership, helping senior leaders achieve their productivity goals through targeted AI applications.&nbsp;



However, the rise in the use of AI in business presents a double-edged sword. While those who become AI champions will thrive, recent research by<a href="https://www.gartner.com/en/newsroom/press-releases/2024-10-22-gartner-unveils-top-predictions-for-it-organizations-and-users-in-2025-and-beyond" target="_blank" rel="noreferrer noopener"> Gartner</a> suggests many organizations will use AI to “flatten their organizational structure” and “eliminate middle management” positions. This rapid evolution is typical in AI, where major milestones now occur within weeks and months, making long-term predictions challenging. Nevertheless, the trend shows that middle managers can remain relevant in increasingly streamlined companies if they evolve into AI-fluent strategic leaders rather than mere coordinators.



<h2 class="wp-block-heading" id="h-develop-an-ai-fluent-workforce-through-practical-application">Develop an AI-fluent workforce through practical application</h2>



The final key to overcoming the AI productivity paradox is developing an AI-fluent workforce. In my experience, traditional approaches to AI training often focus on technical concepts that overwhelm non-technical employees, or generic workshops that don't address specific job functions. This aligns with <a href="https://www.upwork.com/research/ai-enhanced-work-models" target="_blank" rel="noreferrer noopener">the Upwork report's findings</a> that “47% of employees using AI say they have no idea how to achieve the productivity gains their employers expect.” A much better approach is for companies to design AI talent development programs for specific roles and functions so their employees can get practical hands-on training on how to use tools like ChatGPT, Claude and other generative AI tools to do their jobs better, reduce errors and avoid burnout.



This applied learning approach, when guided by AI specialists who understand both the technology and the specific business context, produces employees who understand AI's capabilities and limitations within their particular roles. As a result, the workforce grows to see AI as an influential collaborator rather than a threat or magic solution to every problem. When done right, this shift in mindset will help organizations achieve the desired productivity gains.



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AI investment doesn’t guarantee a productivity gain. Learn why human-centered approaches to AI are key to driving measurable results.

When ChatGPT launched in late 2022, I instinctively knew that the era of traditional knowledge work would soon be over. It was only a matter of | SUCCESS

AI Productivity Paradox: Most Companies Are Using AI Ineffectively

How Your Company Can Use AI Productively | SUCCESS

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Chi Odogwu

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Reimagining Education for Gen Z in the Age of AI

AI Productivity Paradox: Most Companies Are Using AI Ineffectively