Workforce Adaptations in an Automated Environment

Once upon a time, the workplace looked like this: 🔺 A wide base of operators ⬛ A middle of managers 🔝 A small circle of execs at the top making “strategic” decisions And each layer was dependent on the prior layers knowledge and context. But that is no longer the case - AI is cracking that structure apart and now #1 question I get asked is “Where Should AI sit?” I have an entire framework for that, based on trail and error and over 60+ different structures and outcomes across a variety of industries, but to keep it super duper simple, the new mental model is: The Upside Down Pyramid. 🔻 Bottom layer: Automated out. Replaced by RPA, bots, agents. (FYI … Deloitte reports that intelligent automation has led to zero net growth in administrative headcount in over 65% of enterprises) 🧍🏻Middle layer: Thinned out, middle-management pruning some say - as real-time insights and AI copilots give execs direct access to context. They are no longer the widest & thickest structure. 🔝 Top layer: Amplified, not eliminated, with a new diverse set of players at the top. AI translators and cross-functional builders who know tech and business (fyi, Harvard Business Review reported that 42% of managers’ tasks are now deemed automatable—and that number is climbing) In summary: We’re not watching a job extinction event, we’re witnessing an extreme skills migration. 🤯 RECOMMENDATIONS: 1. Redefine your middle. If you’re a middle manager, become the bridge—not the bottleneck. Strategic orchestration beats tactical supervision. 2. Train your top. Your leaders need fluency in AI—not prompt tokens. Nothing is a silver bullet. Invest in simulation-based leadership programs. The new org chart favors the thinkers, the builders, the doers—with AI as their multiplier. Are you adapting to the new shape of work? #FutureOfWork #AITransformation #Leadership #OrgDesign #WorkforceShift #DigitalStrategy #CareerAdvice #DataLeadership >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Worlds 1st Chief AI Officer for Enterprise, 10 patents, former Amazon & C-Suite Exec (5x), best-selling author, FORBES “AI Maverick & Visionary of the 21st Century” , Top 100 AI Thought Leaders, helped IBM launch Watson My 2nd #TEDx talk will be released in 2 weeks!

Post-Acute Care Workforce Data- Analysis of AI’s Potential Impact 1 in every 21 working Americans is employed in the Post-Acute Care industry. In total, this workforce spanning across the segments of Home Healthcare, Nursing Facilities, and Individual & Family Services generally thought of as PAC comprises 7.6 million individuals earning $343.4 billion annually. In the emerging world of AI, this large and unique workforce presents substantial opportunities for efficiency and effectiveness improvement across both Point of Care and Back Office roles. Point of Care (POC) Workforce Total: 6.0M Employees, $257.3B Earnings Home Healthcare: 1.4M, $65.6B Nursing Facilities: 2.1M, $97.9B Individual & Family Services: 2.5M, $93.7B POC Demographics: Most employees fall under “Healthcare Support Occupations,” primarily non-clinical roles like home health aides. "Healthcare Practitioners," such as registered nurses and nursing assistants, form the second-largest group. Additionally, social and community service workers contribute in specific markets. Key AI Opportunities: Ambient Listening: Reduces documentation burden by converting unstructured patient visit conversations into standardized fields. Scheduling & Workforce Optimization: Enhances productivity by efficiently matching caregiver availability with patient needs. Patient & Family Engagement: Expands reach through AI outreach, ensuring continuous patient engagement. AI Impact: Rather than reducing jobs, AI can enhance caregiver productivity, addressing workforce shortages. Even a modest 10% productivity gain could equate to an additional 600,000 caregiver capacity, significantly expanding patient care coverage. Back Office Workforce Total: 1.6M employees, $86B earnings Home Healthcare: 194K, $13.1B Nursing Facilities: 966K, $45.7B Individual & Family Services: 474K, $27.3B Back Office Demographics: This group includes management, administrative, and financial roles, critical to PAC operations across various market segments. Key AI Opportunities: Coding Automation: Streamlines clinical documentation reviews for improved accuracy and reimbursement. Eligibility & Authorizations: Accelerates traditionally manual eligibility and authorization processes. Billing & Collections: Optimizes AR management, accelerating collections from payers. AI Impact: AI presents a substantial opportunity to streamline back-office operations and reduce repetitive tasks. Human leadership will remain essential for strategic management, referral relationships, and payer negotiations, but administrative structures will likely become leaner. Conclusion: The $400B+ PAC industry, crucial for addressing America's aging population, historically has lagged in technology adoption. However, increasing workforce constraints and growing patient demands will accelerate the integration of AI at a scale of tens of billions of dollars of impact, transforming both patient care and business operations.

Spire.AI Launches AI Agent Sigma™ for Autonomously Delivering Talent Supply Chain Excellence. Read the full press release here - https://lnkd.in/gwzDEJKt To build a truly agile organization, leaders need more than workforce insights—they need execution. Business priorities shift in real time, and talent decisions should keep pace. The ability to mobilize skills, align talent with evolving needs, and proactively shape workforce strategy is what will define future-ready organizations. This is where we see the future of workforce transformation heading—with AI that not only understands skills but dynamically aligns talent with evolving priorities. With that vision, we’re introducing Agent Sigma™—an autonomous AI agent built to act. Agent Sigma™ continuously interprets, adapts, and drives talent decisions in real time. It ensures that skills are identified, mobilized, and deployed where they have the most impact—before the need even arises. Consider this scenario: A global insurance company expanding digital claims processing faces challenges in workforce planning, skills assessment, and hiring for claims adjusters and fraud analysts, leading to inefficiencies and higher costs. An autonomous AI agent could map current workforce skills to emerging roles, identify employees with adjacent skills in risk assessment and financial analysis, and upskill them for digital claims positions. By mobilizing internal talent instead of hiring externally, the company accelerates training, seamlessly transitions employees into high-impact roles, reduces costs, improves service speed, and future-proofs its workforce. This shift transcends efficiency. It's about building an inherently adaptive workforce that evolves in sync with strategy and is consistently prepared for future demands. For enterprises, this enables: ▪️Workforce agility that matches business velocity ▪️Proactive talent mobility that reduces reactive hiring ▪️AI-driven execution that transforms strategy into action The future of workforce strategy isn't about processing more insights—it's about autonomous orchestration that keeps your talent ecosystem perpetually aligned with opportunity. How do you envision autonomous AI reshaping talent strategy in your organization? Let's explore this evolution. #WorkforceStrategy #FutureOfWork #TalentInnovation #AIforTalent #SkillsIntelligence #AIAgent #AgenticAI #TalentStrategy #AIinHR #HRTech #TalentTech #AI #SpireAI Spire.AI Copilot for Talent