Digital Workforce Optimization

I've spoken with countless CEOs who recognize digital labor as essential for staying competitive—but struggle with where and how to start. At Asymbl, we're already actively using digital labor to enhance our own workforce. Our Agentforce SDR Agent, whom we've named Theodore Frank, and our Asymbl Recruiter Agent are integral members of our team. Follow my content to hear our real-world experiences and insights—not just theory. Onboarding digital labor is similar to hiring human talent. It doesn't have to mean massive organizational disruption, but it does require thoughtful planning and execution. This is how we approached it: #1 We started with a business challenge.  → We identified a real problem we wanted to solve, just as we would when deciding to hire someone new. → Our goal wasn't simply to "implement AI," but to address specific, meaningful challenges faster and more effectively. #2 We defined the role clearly.  → We outlined exactly what this position would do. → We specified their duties, performance metrics, and expected outcomes. → We considered human-equivalent labor costs to establish a budget. #3 We planned our training strategy.  → We determined how our digital employee would acquire its knowledge, how it should behave, and how it would interact and collaborate with our existing human teams. #4 We onboarded our digital employee.  → We selected and configured the right digital employee—whether using pre-built solutions like Asymbl’s Recruiter Agent or Salesforce’s Agentforce SDR Agent, or creating a customized digital employee tailored to our business. → Onboarding involved integrating the digital employee into our processes, reflecting the detailed considerations from our training strategy. #5 We enabled it effectively.  → Much like setting a human employee up for success, we enabled our digital employee by assigning clear initial tasks. → We regularly reviewed outputs to ensure accuracy, quality, and alignment with our organization's standards and communication style. #6 We supervise and coach continuously.  → Digital employees require ongoing management and oversight just like humans. → Our VP Revenue, Ken, now reviews Theodore’s performance weekly and provides coaching to continuously improve his effectiveness in interactions with prospects. One difference with digital employees compared to human employees is that providing feedback and coaching requires updating the underlying technology and training data, rather than simply having a chat. Having a structured technical plan and the right partner to guide this process is crucial. That's exactly what Asymbl does through our digital labor activation practice. Digital labor isn't future speculation—it's already here, reshaping how we work. Our team, including our digital teammates, continues to expand, and I'll be sharing more stories and insights as our journey progresses. #digitalemployee #futureofwork #aiagent

This $1B retail business saves $7M/year with digital workers running their logistics. Avrora is the biggest multimarket chain in Ukraine. 460 new stores opened in one year. 500+ more planned. But logistics was becoming the bottleneck. When you're opening 460 stores you can't afford that. Every day something slips - a carrier doesn't show up, a rate wasn't compared properly, a tender sits for hours because someone was on another call. So they plugged in our digital workers. 14 of them. They handle the full cycle now - publish tenders automatically, reach out to carriers across every channel, collect bids, rank them by price and reliability and past performance, recommend the best option. Human just approves with one click. Docs, tracking, payment - all runs on its own. After one year: $7M+ saved on transportation costs. 75,000+ tenders processed. 96.24% tender acceptance rate. 385+ active carriers - 44 of them new, onboarded through our network. And the stores kept opening. Logistics isn't the bottleneck anymore. It's the engine. And honestly I think this is what every logistics operation will look like in the future. A digital team that actually runs your business while you grow it.

𝗧𝗵𝗲 𝗛𝘂𝗺𝗮𝗻 𝗟𝗼𝗼𝗽 𝟭𝟯: 𝗦𝗼𝗹𝘃𝗶𝗻𝗴 𝘁𝗵𝗲 𝗟𝗮𝘀𝘁 𝗠𝗶𝗹𝗲 𝗼𝗳 𝗔𝗜 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 Most organizations are finding themselves pilot-rich but transformation-poor. They have hundreds of active AI deployments, yet these often remain isolated islands of productivity. A recent Harvard Business Review piece by Karim Lakhani at Harvard Business School, Jared Spataro at Microsoft, and Jen Stave, PhD at Harvard Business School points out that the primary obstacle is rarely model quality or data availability. The real bottleneck is the last mile of transformation where technical capability must meet organizational design. To move from localized experiments to a truly AI-native operating model, the authors outline a crucial blueprint for integrating agentic workflows: - 𝗖𝗹𝗲𝗮𝗻-𝗦𝗵𝗲𝗲𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗥𝗲𝗱𝗲𝘀𝗶𝗴𝗻: Companies must stop bolting AI onto legacy workflows. Instead, processes need to be mapped out from scratch by asking how they would be built today with modern AI agents. - 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗖𝗮𝗽𝘁𝘂𝗿𝗲: Tribal knowledge must be treated as a strategic asset and externalized. Organizations need to pair senior experts with designers to codify their unique judgment into digital systems. - 𝗠𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲: The focus must shift from standard model governance to agent governance. Agents should be treated as a managed workforce, utilizing centralized control planes to monitor performance, security permissions, and accountability. - 𝗥𝗼𝗹𝗲 𝗥𝗲𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗖𝗮𝗿𝗲𝗲𝗿 𝗣𝗮𝘁𝗵𝗶𝗻𝗴: As AI absorbs execution tasks, human roles must shift toward design, orchestration, and interpretation. Firms are already beginning to assign managers to oversee digital workers just as they would human teams. The technology is ready, but the challenge for today's executives is deciding if they are willing to fundamentally redesign the organization to realize its full potential. This is essential reading for anyone leading an AI transition. Link: https://lnkd.in/gMmChfNK #TheHumanLoop #GenerativeAI #AIStrategy #ChangeManagement #FutureOfWork #AgenticAI #OrganizationalDesign #BusinessTransformation #TechLeadership #DigitalWorkforce #HarvardBusinessReview #ProcessRedesign #AIIntegration #MachineLearning #SystemDesign #Innovation

How to Get 10X More Productivity 🚀 The way we build teams is broken. For decades, org charts grew by adding headcount. If you needed more output, you hired more people. But that model is collapsing: • Budgets are flat or shrinking • Productivity growth is stagnating • Most employees spend 40% of their time on repetitive tasks (Deloitte) At the same time, the opportunity has never been bigger: • AI can now automate 60–70% of knowledge work tasks (McKinsey) • Early adopters see 20–30% productivity gains in year one • One person, with the right digital workforce, can match the output of an entire department => This is the rise of the digital worker: AI copilots, agents, and automations that sit alongside humans as part of the org chart. Hiring in the Age of Digital Workers When you hire someone today, you’re not just hiring a single individual. You’re hiring a conductor of an orchestra of AI resources. Take marketing as an example: Hiring one marketer should mean bringing in someone who knows how to activate AI agents for content, social, SEO, ads, analytics, personalization, and more. One human → multiplied by dozens of digital workers. Now extend that logic: • A finance hire who commands AI for forecasting, compliance, and reporting • An operations hire with AI copilots for supply chain, scheduling, and workflow optimization • A sales hire backed by AI prospecting, outreach, and CRM automation 5 Principles for Building a 10x Org in 2025 1️⃣ Hire for orchestration, not execution Your team should be experts at leading digital workers, not drowning in manual tasks. 2️⃣ Expect leverage, not headcount One skilled human + AI = output of 5–10 traditional FTEs. 3️⃣ Prioritize adaptability Tools will change fast. What matters is the ability to design workflows where AI compounds human creativity. 4️⃣ Measure outcomes, not hours Redefine productivity in terms of revenue, margin, CAC, cycle time, and customer experience — not time spent. 5️⃣ Redraw your org chart Start with the human role at the top, then map the AI digital workers that multiply their output. That’s your real architecture of the future. Next time you ask, “Should we hire one person?” Ask instead: “What digital workforce comes with them and how much more can they deliver from day one?” This is not the future. It’s the architecture of hiring today for any startup. Or any company that wants 10x productivity. If you had to hire one role right now, with 10x productivity in mind, which would it be? Drop your comment below and let's have a discussion. #AI #Productivity #Hiring #Career

93% of Fortune 500 CHROs now use AI in HR operations yet 70% of employees still lack clear AI guidelines at work according to Gallup... The AI revolution in People Operations isn't coming, it's here and accelerating exponentially. While executives race to deploy AI solutions, a massive execution gap is creating both opportunity and chaos. Today we analyzed the five strategic AI deployment models that elite organizations are using to transform their workforce architecture. 🎯 The Five AI Models Reshaping People Strategy: 1.) AI Co-Pilots Digital assistants to boost manager effectiveness and decision-making. Humans drive culture, engagement, and leadership. Think Lattice, Culture Amp, Leapsome. 2.) AI Solutions Purpose-built platforms for HR data, compliance, and talent management. You focus on aligning strategy and enabling teams. Think HiBob, Personio, Workday. 3.) AI Workers Hire digital recruiters, engagement bots, or predictive models instead of adding headcount. You handle human oversight and fairness. Think pymetrics (now Harver), Hirevue, SeekOut. 4.) AI Workflow Builders Platforms to automate HR processes and connect systems. You manage HR tech engineering and integration. Think Zapier HR, Tability, n8n 5.) DIY on LLMs Build with APIs to create custom HR apps and analytics. You drive innovation in HR data and workflows. Think OpenAI HR APIs, Hugging Face (HR-focused). The breakthrough insight? Top-performing organizations don't choose one model. They orchestrate all five strategically, creating AI-powered People Operations that deliver measurable competitive advantage. But here's the reality check: Only 15% of employees understand their company's AI strategy, and 76% of HR leaders believe organizations without AI adoption in the next 24 months will lag behind competitors. 🚀 The Strategic AI Acceleration Playbook → Map Your AI Stack: Audit current processes against the five models to identify integration gaps → Layer Smart: Start with operational solutions, then add co-pilots and custom development based on workforce maturity → Build AI Governance: Establish frameworks for ethical deployment and bias monitoring in people decisions This transformation is creating a new category of competitive advantage. At PeopleAtom, we're building the community where visionary CXOs, founders, and People leaders collaborate to navigate this complexity and turn AI adoption into market differentiation. Ready to architect your AI-powered workforce strategy? Join forward-thinking CXOs, founders, and People leaders who are shaping the future of work (Apply for an invite, link in comments) What's your biggest AI opportunity in workforce transformation right now? Love the evolution, Joe

Most organizations treat workforce strategy like a headcount exercise. How many people do we need, where do we put them, and what do we pay them? That worked when jobs were stable, skills were predictable, and "digital labor" meant a spreadsheet. It doesn't work when AI can do 30% of your team's tasks by Tuesday. In a recent conversation with Bob Pulver on his podcast, Elevate Your AIQ, I kept circling back to a framework from our book, Humanizing Human Capital, with Dr. Solange Charas, which we think holds up even better now than when we wrote it. We call it the 4 Ws: 🔹Work is the problem to be solved, not the job descriptions on file. Most orgs still design roles around tasks. AI doesn't care about your org chart. It cares about outcomes. If you haven't redefined what work actually means in your organization, you're optimizing around the wrong unit. 🔹Workforce is the full mix of who and what does that work: employees, contractors, partners, and increasingly, digital labor. The question isn't "how many FTEs do we need?" It's "what's the right combination of human and non-human contributors to get this done well?" 🔹Workplace is the systems, tools, norms, and environments that make the work possible. You can have the right people doing the right work and still fail if the infrastructure around them creates friction instead of flow. 🔹Worth is the value exchange. What people contribute, what they receive, and whether they believe it's fair. This is the one most organizations get wrong first. When productivity gains go entirely to the company and none to the people who produce them, trust erodes quickly. When these four are aligned, strategy moves. When they're not, AI amplifies misalignment. In my experience, Worth is the W breaking down fastest right now. Companies are asking people to do more, learn faster, and adapt constantly, while the compensation models, career paths, and recognition systems haven't moved at all. That's a design and orchestration problem. Which of the 4 Ws feels most out of sync in your organization? 🎧 Full conversation with Bob Pulver on Elevate Your AIQ: https://lnkd.in/ekuDjnyT #HumanizingHumanCapital #WorkforceStrategy #FutureOfWork