Background

This paper began as a summary of a 3-day private equity investment research project for The Abernathy Group Family Office. During the trip, as research advanced, we realized the changes available and likely to be implemented are far larger and potentially more disruptive than believed when I got on the plane.

The primary goal was to find out whether changes to America’s educational infrastructure would welcome the changes being introduced by leveraging newly available technologies. The secondary goals were to understand how and when the technologies would best be introduced and implemented, or whether our ineffective, staid educational system would remain unchanged.

The founders/owners of the private university welcomed the visit, and as conversations began, it became clear I was outside my “circle of competence.” It became obvious that shifts in education, healthcare, and many other educational verticals will restructure our economy in ways not seen since the Industrial Revolution.

I needed to grasp the major shifts, dislocations, and demands education must meet to educate our young adults and maintain our country’s place in the world order. Here’s why.

Education has been, and remains, one of the most relevant indicators of economic prosperity. Education is key to maintaining our globally advantaged position. Our U.S. educational system must incorporate the financial and technological changes driven by emerging technologies over the next few years, or risk losing our standing as a global hegemon.

Because of this realization, the goal of this paper has shifted to answering the questions educational industry experts are, and will be, asking about the future before us.

Note: I have likely overlooked many important questions critical to unlocking the future of education. However, here is my first humble list of the questions that need answers so far.

Partial List of Questions Needing Answers Before Making Decisions

• What will the job market demand of employees and management over the next 10+ years?
• Which of those jobs will require basic degrees, advanced degrees, or certificates, as opposed to demonstrated competencies?
• How will the delivery of education change with the soon-to-come implementation of virtual reality (VR), augmented reality (AR), and 6G connectivity, combined with edge computing?
• What will the teacher’s role become when each student has Ph.D.-level data at their fingertips that never tires and always provides (largely) reliable results?
• How will changes in the hiring process influence education’s delivery? (This is a second-order benefit/effect for many educational institutions, as they may be rated by their job placement statistics.)
• How quickly will Artificial Intelligence (AI) change the implementation and delivery of education?
  • Change too fast, and our economy enters a recession as worker displacement will outweigh Artificial Intelligence’s benefits. (*This also risks creating long-term rejection of this transformational technology, potentially souring the citizenry’s opinion of Artificial Intelligence.)
  • Change too slow, and the U.S. economy will decline into a recession as corporate earnings lag the enormous spending required to create Artificial Intelligence; also, rival countries (China, for instance) are already reaping the benefits of a more educated society (6 days a week, no summer holiday for young students).
• What impact will educational change have on the existing institutional infrastructure already in place in the U.S. and globally?

1.  The Pedagogical Imperative: Solving the Scalability Crisis

The global educational landscape is undergoing a wholesale transformation. Education and the learning model are moving from the current industrial “mass-produced” model to a personalized, scalable “Tutor Model” powered by artificial intelligence (AI). Organizations will soon be fundamentally rewiring their pedagogical contracts to capture education’s long-term strategic value and adopt the technological advantages of a) virtual reality (VR), b) augmented reality (AR), c) 6G, and d) A.I., thereby transitioning from a legacy of standardized instruction (1 teacher to 30/40 students) to a high-touch educational ecosystem (Mastery-Based Learning) that delivers near one-to-one delivery of education (the Tutor-Student model) at scale.

Research clearly confirms that this evolution is an essential requirement for global economic resilience. Traditional 1-teacher-to-30-student systems were never designed for the accuracy required in a post-industrial economy; the 1-to-30 model often traps students in an “intervention purgatory” where progress stalls because of fragmented data, delayed feedback, and social and peer pressures, all compounded by limited teacher bandwidth. The strategic foundation of this evidence-based shift in delivery methodology lies in resolving Benjamin Bloom’s “2-Sigma Problem.” Bloom’s 1984 research proved that students receiving one-on-one tutoring combined with mastery-based learning (MBL) performed 2 standard deviations (2SD) better than those in traditional classrooms. Students reached the 98th percentile faster and with fewer hours of concentrated instruction.

The problem, both societally and economically, was that tutor-based education was so expensive that it was available solely to the elite, which tended to create, widen, and sustain a class system. Although scaling human-to-human instruction has traditionally been costly, integrating Generative AI (GAI) and Analytical AI offers the first practical approach to democratize and scale this “Tutor Model” across the global Total Addressable Market (TAM) at equal or lower cost.

Traditional Classroom – delivers 50th-percentile success; largely available everywhere today.

Mastery-Based Learning (MBL) – delivers 84th-percentile success; not widely available, as it requires differentiated group instruction that prohibitively increases costs.

AI-Powered Tutor (GAI; AI + Human Hybrid Model) – delivers 90th-percentile success; not widely available today; yet gaining traction experimentally at costs similar to the current Traditional Classroom model.

2.0 sigma type instruction – 93rd to 98th percentile success; Not widely available today; (includes AI Scaffolding + Human Mentorship)

The mechanics of this shift are defined by the “Mastery-Based Learning” framework, which fundamentally reconfigures the credentialing system through the following structural changes:

1. The Mastery Floor: A 90% comprehension threshold ensures students advance only after demonstrating deep competency, preventing learning gaps from compounding through near-instant feedback when a lack of understanding is evident. This is “Competency-based Progression.” (Grading changes: instead of starting at 100% and subtracting for each wrong answer (thus creating negative feedback), MBL starts at 0% and adds to the score, allowing successful answers to reinforce positive feedback.)
2. Competency-Based Progression: Shifting the credentialing framework from a time-based (calendar-driven) system to a competency-based (demonstrated-skill-driven) model, reinforced with real-time instruction while the topic is fresh and in focus.
3. Variable Time, Fixed Outcomes: Reversing the industrial model of “fixed time/variable outcomes” to a superior “variable time/fixed outcomes” model delivers high-quality learning for every participant. Teachers and instructors must, however, mitigate the “Critical Thinking Paradox.” Students may achieve higher assessment scores with AI assistance while simultaneously experiencing a decline in deep conceptual understanding and emotional IQ. Addressing this risk is a top-tier management priority for educational institutions seeking to preserve first-principle innovation.

2.  Labor Market 2030: Mapping Education to Economic Demand

By 2030, the global labor market could undergo a massive reconfiguration. Estimates suggest that while approximately 92 million jobs could be displaced, the creation of 170 million new positions will result in a net increase of 78 million jobs.

This rebalancing will likely shift both hiring volume and categories; nearly 40% of demand for workers’ core skills is expected to change within the decade. Educational institutions must pivot immediately to meet the “velocity of talent demand” or undergo major economic misalignment. To support employee profitability in the 2030 economy, educational pathways must correspond with the following trajectories (below are just a few seemingly obvious examples):

Potentially High-Growth Demand Occupations

AI and Machine Learning Specialists; Prompting Engineers; Fintech and Renewable Energy Engineers; Sustainability Specialists and Administrative Leads; Nursing Professionals and Secondary Teachers (Driven by demographic shifts in aging and growing populations)

High-Displacement Occupations

Data Entry Clerks and Bank Tellers; Graphic Designers and Legal Secretaries (High-level knowledge work being automated by GAI); traditional manufacturing (non-automated) and postal clerks. This labor shift accelerates the credentialing revolution, where micro-certifications challenge the dominance of the four-year degree cycle

Hiring Changes will Demand Educational Changes

Changes to Employer Preference: 74% of employers now favor candidates with verified digital credentials for AI roles over those with traditional degrees alone. This will shift the emphasis from “who you know” or which school you attended to “demonstrated competencies,” while avoiding the legal risks of DEI lawsuits. Hiring Efficiency: Research shows skills-based hiring can reduce time-to-hire by 28% and boost role-match quality by 35%. These financial stresses suggest that the human element becomes the key factor in the transition, especially the teacher’s role.

3. The Professional Metamorphosis: Teachers as Learning Architects

The transition to an AI-augmented environment requires a professional metamorphosis for educators, shifting their role from lecturers to “Learning Architects” and “engagement coaches.” By automating monotonous administrative and grading tasks, educators can reclaim 20% to 30% of their time, allowing them to focus on mentorship and deeper cognitive development. The “Human-in-the-Loop” requirement is the strategic pillar of this metamorphosis. The teacher of the future must pivot toward roles AI cannot duplicate, focusing on:

Emotional Intelligence (EQ): Reading subtle social cues and personal situations to drive motivation, engagement, and holistic development. Targeted Intervention: Using analytical AI data to provide surgical support for students at risk of “intervention purgatory.” When students lack understanding, instant intervention accelerates learning and significantly increases understanding and intelligent application. Critical Thinking Safeguards: Actively challenging students may help prevent the “Critical Thinking Paradox” mentioned earlier.

Three strategic tasks define the Teacher-AI Collaborative Workflow:

1. Data-Driven Intervention: AI identifies specific learning gaps in real time, allowing the teacher to provide targeted, data-backed support when the topic is fresh and concentration is high.
2. Creative Lesson Design: Using GAI to generate personalized teaching and custom rubrics, enabling personalized materials at scale.
3. Ethical Authority: Instructors must serve as the final authority on AI outputs, questioning AI-generated results to ensure technology does not reinforce bias or undermine students’ conceptual reasoning.
4. “Technological Self-Efficacy” is vital for teacher retention: educators who feel empowered by these tools report significantly higher professional satisfaction, which is essential as the remote learning ecosystem expands into homes.

4. The Remote Learning Infrastructure: Parental Support and Digital Access

The domestic environment has become a critical strategic node in the educational supply chain. Parental support is no longer a peripheral benefit; it is a core requirement for the success of the remote “Tutor Mode.” To fulfill educational and financial goals, the home must be optimized as a high-fidelity learning site. Parents must provide the Technical Foundations and the discipline required to bridge the “Digital Divide”:

Reliability: Securing high-speed, consistent internet access as an always-available utility is increasingly important and may be critical to future educational infrastructure. Device Management: Providing hardware that can support immersive VR/AR and advanced AI interfaces. These technologies, though still in the lab, will enable education to become “immersive,” and may lead to additional learning and creative efficiencies.

Digital Competence: Developing the family’s competence to navigate AI platforms and evaluate tool effectiveness will be necessary. In remote settings, the “Human Element” is the home’s primary value. While the AI tutor handles technical skills, parents serve as the main facilitators of irreplaceable skills—such as critical thinking, creativity, moral judgment, emotional “IQ,” and discipline. These skills must develop outside education’s digital interface. Educators must recognize that parental support is necessary for impartial access. They must hold parents and caregivers accountable. Without improving domestic infrastructure, the digital divide will remain a structural economic disadvantage.

5. Economic & Strategic Realities: Scaling the Intelligent Classroom

The economics of education are shifting from high-overhead physical infrastructure to scalable, remote, digital-first models. This transition represents a massive CAPEX reduction for institutions, allowing them to redirect capital from physical infrastructure and maintenance to talent development and technology scaling. Research shows that a cost-benefit analysis of “Virtual vs. Traditional” demonstrates a substantial reduction in the cost per student for the intelligent institution.

• 6G technology will enable the strategic delivery of this high-fidelity content. The shift to 6G is a technical prerequisite for interactive education for several reasons:
  • Sub-millisecond latency is necessary to eliminate motion sickness in VR and allow real-time haptic feedback in medical and surgical training. It can also enable more remote training, improve understanding and tactile skills, and reduce training costs for education that requires physical interaction.
  • Signal Fidelity: 6G. Denoising procedures reduce the Bit Error Rate (BER) from 0.19 to 0.12, guaranteeing the signal reliability required for complex, high-stakes immersive simulations.
• Peering ahead to 2030, the “Known Unknowns” remain the primary barriers to global leadership. The lack of uniform AI literacy metrics and the fast pace of talent demand mean that continuous upskilling may become the ultimate competitive advantage in the new economy. Displacement, rather than job loss, will become the reality.
  • This generates a significant unmet educational need for educational institutions. Educational organizations that pursue “wholesale fundamental change” rather than incremental use cases could realize the full profit potential of the intelligent era.

As the half-life of skills shrinks, micro-certifications and demonstrated competencies are supplementing traditional four-year degrees.

Employer Preference: 74% of employers prefer candidates with verified digital credentials for AI roles over those with traditional degrees. Skills-First Hiring: This approach lowers time-to-hire by 28% and improves role-match quality by 35%.

Summary

The educational system must rethink and reshape itself over the next decade. Sooner rather than later. Looking forward. What is to come?

• Educational institutions are still needed, yet must welcome the technologies becoming available today and in the near future (AI, AR, VR, 6G), delivering deeper, faster learning at lower cost with more definable outcomes.
• Teachers’ skills must evolve; Artificial Intelligence must become part of every educational infrastructure. Teachers need to become more like coaches than lecturers. They will spend less time grading papers and more time identifying opportunities to motivate students. “Specific Intervention” will immediately identify misunderstandings of concepts and applications when the topic is fresh. “Focused Support” increases mastery while decreasing costs, confirming that students truly understand and can apply the material.
• Remote delivery of education leading to certification will become commonplace and well received. This will disrupt the hiring process. (See Khan Academy and Alpha Schools for vivid examples of education’s future (today). (This Alpha School YouTube segment is a must-view.)
• Hiring candidates based on merit and skills will become the norm. This will substantially disrupt today’s brick-and-mortar educational system. It is likely that “credentialing,” “certification,” and “outcome-based” hiring will become standard, as employers demand the “show me what you can do” hiring method, as opposed to the “who referred you,” “who you know,” or “what school did you attend” process. (What will happen to the brick-and-mortar infrastructure?
• “Displacement vs. job loss.” The need for “evergreen” education, which enables the workforce to continually upgrade skills, will also become commonplace, creating new opportunities for digitally superior educational facilities.
• The infrastructure required for education will be upended. Vast structural demands will give way to lower-cost, remote facilities. This will significantly affect today’s education system, much as Amazon’s impact on retail infrastructure did. The potential downside of this structural change is that social skills may be less well developed, isolation may become an emotional hurdle, and feelings associated with friendship and bonding could suffer. (However, university infrastructure may have more pickleball courts 😊)

For those interested in investing in the educational category:

Jobs with a high probability of existing in 10 years:

• Jobs requiring high-stakes accountability and complex human judgment will remain in demand.
• Human dexterity will also be in demand, along with the soft skills of empathy and emotional accountability.
• Jobs that will survive are most likely to require skills AI can’t deliver, namely those that require empathy, demand high-risk decision-making, creativity, and involve physical dexterity and unpredictability. Examples:
• Healthcare professionals
  • Nurses (master’s, doctoral degree, or national certification);
  • Surgeons (doctoral degrees with 4-8 years of fellowship);
  • Physician Assistants (master’s degree and state licensure);
  • Mental health Counselors/Psychologists/Psychiatrists (master’s degree, doctoral degree and/or clinical licensure);
• Engineers and physically unpredictable demands
  • Renewable Energy Engineers; Solar Engineers; Wind Engineers.
  • Electricians, Plumbers (and all essential infrastructure needing vocational certifications and apprenticeships)

Jobs likely to become obsolete (or lessened) in 10 years:

• Data-heavy tasks (filling in spreadsheets, some coding) and repetitive tasks.
• Administrative and office support jobs; executive assistants; bookkeepers and Payroll clerks; data entry clerks.
• Transportation and logistics
• Long-haul truck drivers involved in highway driving (last mile may still require specialized and certified skills;
• Delivery Drivers (drones and sidewalk robots)
• Warehouse workers (robots)
• Assembly line workers
• Basic Content Creation and Basic Research
• Basic technical writers
• Proofreaders and copy editors
• Legal assistants
• Customer Service and Basic Retail employment
• Cashiers
• Customer support and client service
• Telemarketers

Questions remaining and topics not covered or needing more follow-up due to the rate of change:

• Will the U.S. move from a severance-based model (paying severed employees a monetary sum intended to carry them through the job-seeking process) to an educational package designed to reskill the employee relative to the available job market and to the severed employee’s request at the time of severance?
• If yes, will this create a new educational system with an imperative to reskill a displaced workforce and ensure former employees are better equipped for the future? (This type of on-demand education is likely to be credential-based and will reach scale (profitability) only if we move to the MBL and tutor/student model. This could be a HUGE market opportunity, creating a huge industry…)

Disclaimer: The materials and topics discussed reflect the views of the Abernathy Group II Family Office and are provided for members of the Family Office community. These topics and materials do not constitute a recommendation or solicitation of any products or services. The information may be based on data from external sources deemed reliable; however, we may not be able to verify it. We make no warranty, express or implied, regarding accuracy or completeness. This material may not be updated in the future. Any opinions and estimates included herein represent our judgment as of this date and are subject to change without notice.