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

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

You can't hire 300,000 workers who don't exist. Infrastructure Australia just confirmed what we've known was coming: workforce needs to double by 2027. Brisbane 2032, 1.2M new homes, AUKUS, energy transition. All competing for the same shrinking labour pool. But here's what the report also says: productivity improvements are the answer, not just more bodies. Every major project currently burns worker hours navigating compliance mazes, chasing approvals, and coordinating between siloed systems. That's where the doubling happens. Not in workforce size, but in what each worker can actually deliver. We've been positioning governance-integrated digital twins for exactly this moment. Not as a technology play, but as a workforce multiplier. When Brisbane City Council reviews a development, when Arup delivers Olympic infrastructure, when tier 1 contractors bid on energy projects... the teams that can automate the governance complexity will win. The procurement shift from Dubai, Abu Dhabi and now Madrid (all using building approval automation) to Australia (Brisbane 2032 pressure) isn't coincidence. It's necessity becoming very visible. The workforce crisis just made digital twins non-negotiable. What productivity constraints are you seeing in your projects right now? https://lnkd.in/gpmdwmBg

Bridging Talent Acquisition & Succession Planning – Powered by Digitalization & Automation In my current personal research, I’m exploring how organizations can break the traditional silos between Talent Acquisition (TA) and Succession Planning. When these functions are integrated — and empowered by modern digital tools — they create a unified, proactive strategy for sustainable talent growth. Preliminary findings show that the link delivers: • Proactive Hiring: Predictive analytics help TA teams identify candidates who fit current needs and have future leadership potential. • Future-Ready Workforce: Digital succession platforms provide a transparent, data-driven leadership pipeline. • Lower Turnover Risk: Automated career-pathing boosts engagement by mapping clear growth opportunities. • Organizational Agility: When critical roles open unexpectedly, automation enables instant matching of internal talent. Emerging best practices from the research include: - Integrating digital succession planning platforms directly with the ATS. - Leveraging AI-driven assessments to measure current and future potential. - Automating reporting to keep TA, L&D, and leadership aligned. - Using workforce analytics to forecast and address skills gaps before they appear. Key insight: When TA and succession planning are digitally connected, hiring evolves from a reactive task into a strategic, automated pathway for building tomorrow’s leaders. As part of my research, I’d love to hear from you in DM: How is your organization using digitalization to link hiring today with leadership needs for the future? #HRResearch #TalentAcquisition #SuccessionPlanning #DigitalHR #Automation #LeadershipPipeline #FutureOfWork

Digital labor can unlock unlimited potential for every organization across industries. Recent Salesforce research shows that 86% of CHROs say integrating it will be a critical part of their job in the years ahead – but just 15% of organizations have fully implemented agentic AI. Leaders recognize the potential of agents in the workplace, but often lack a clear roadmap for where to begin. That’s why Salesforce announced our Workforce Innovation Playbook – a step-by-step guide designed to help any organization successfully integrate agents into the workplace. The playbook outlines the four-part framework we’ve created and implemented at Salesforce - and have been evangelizing to our customers - to help organizations across industries on their digital labor transformation: Redesign: The first step is designing new ways of working that pair AI speed and scale with uniquely human traits like creativity and judgement. Companies must reimagine jobs and workflows to optimize collaboration between humans and agents, including automating manual tasks and allowing employees to focus on complex, high-impact work. Reskill: Preparing employees for agentic AI has never been more urgent to the success of the future workforce. Organizations must create skills-based learning opportunities to support employees’ transition to new roles with agents. Redeploy: Digital labor can take on tasks and sometimes jobs of people – and at the same time, will create entirely new tasks and jobs, some of which we have yet to imagine today. This will require companies to take stock of their priorities and future growth opportunities, and redeploy talent to critical roles based on skill and experience matching. Rebalance: A human-agent workforce is constantly evolving and requires continuous monitoring and adjusting to keep up with the pace of innovation and evolving business needs. Rebalancing is a dynamic process of adjusting roles and responsibilities as agent capabilities evolve – ensuring people and AI are doing what they do best. I invite you to explore the Workforce Innovation Playbook and join us in building a human-agent workforce, together!  https://lnkd.in/gnChHzZA All built by this amazing team Austin Jackson, Ali Badibanga, Ed.D. Giulia Sergi, Marcus S., Elizabeth Patterson, Ph.D., PMP, Sanjeev Sharma, neelima vojjala, Amanda-Rae Barboza Barela, PMP, Annika Ekblad, Jada Garrett, MBA, PMP, CSM, Mandie Lupone Sarah Shahid Emily (Wiser) Marshbank Victoria Kumper

𝗡𝗲𝘄 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗷𝘂𝘀𝘁 𝗱𝗿𝗼𝗽𝗽𝗲𝗱 𝗼𝗻 𝗔𝗜 𝘄𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻. Built on analysis of 1,000+ tasks across 25 key roles in technology and business services, the research reveals stunning productivity potential: ↳ 70-80% uplift in business process services ↳ 50-60% uplift in software development ↳ 45-50% uplift in infrastructure services ↳ Real case studies showing 80% headcount reduction in AI-augmented operations 𝗧𝗵𝗲 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗶𝘀 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗮𝗰𝗿𝗼𝘀𝘀 𝟱 𝗰𝗼𝗿𝗲 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝘁𝗵𝗲𝗺𝗲𝘀: 1. 𝗗𝗲𝗰𝗼𝘂𝗽𝗹𝗶𝗻𝗴 𝗦𝗰𝗮𝗹𝗲 𝗳𝗿𝗼𝗺 𝗦𝗶𝘇𝗲 → Growth is no longer tethered to hiring curves. AI is severing the link between revenue and headcount, shifting from effort-based to outcome-linked pricing. 2. 𝗙𝗮𝘀𝘁 𝗙𝗼𝗿𝘄𝗮𝗿𝗱, 𝗕𝘂𝗶𝗹𝘁 𝘁𝗼 𝗟𝗮𝘀𝘁 → AI boosts productivity, but value realization requires deliberate role reconstruction. The challenge isn't tech readiness—it's people readiness. 3. 𝗕𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗟𝗮𝗱𝗱𝗲𝗿 → Linear career paths are broken. Career progression now looks like a lattice—fluid, skill-led, nonlinear, where skill density beats seniority. 4. 𝗛𝘆𝗯𝗿𝗶𝗱 𝗧𝗲𝗮𝗺𝘀 → The future is Humans + AI agents working in delivery pods. Performance models and governance structures must catch up to this new reality. 5. 𝗥𝗲𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗦𝗼𝗰𝗶𝗮𝗹 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁 → AI isn't just a technology shift—it's a structural reordering of work, value, and institutions that extends beyond enterprises. 𝗔𝗰𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝘁𝗼 𝘁𝗵𝗲 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵, 𝘁𝗵𝗲𝗿𝗲 𝗮𝗿𝗲 𝟲 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗺𝗼𝘃𝗲𝘀 𝘆𝗼𝘂 𝗺𝘂𝘀𝘁 𝗺𝗮𝘀𝘁𝗲𝗿 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗮𝗻 𝗔𝗜-𝗳𝗶𝗿𝘀𝘁 𝘄𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲: ⬇️ 𝟭. 𝗜𝗹𝗹𝘂𝗺𝗶𝗻𝗮𝘁𝗲 𝘁𝗵𝗲 𝗽𝗮𝘁𝗵 → Move from awareness to a clear, anchored AI vision across the enterprise. 𝟮. 𝗕𝘂𝗶𝗹𝗱 𝘁𝘄𝗼 𝗰𝗹𝗼𝗰𝗸𝘀 → Balance short-term productivity gains with long-term capability building. 𝟯. 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝘁𝗵𝗲 𝘀𝗵𝗶𝗳𝘁 → Redesign work, roles, and accountability around Human + AI collaboration. 𝟰. 𝗟𝗲𝗮𝗱 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗲𝗱𝗴𝗲 → Model the change, relearn, and rewire culture from hierarchy to ecosystem. 𝟱. 𝗚𝘂𝗮𝗿𝗱 𝘁𝗵𝗲 𝗰𝗼𝗿𝗲 → Embed ethics, governance, and human judgment at the center of AI systems. 6. Reimagine the system → Extend AI transformation beyond the enterprise into education, policy, and society. 𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵: Organizations are moving from traditional pyramid structures to diamond-shaped models—lean entry-level layers, empowered middle management, and hybrid Human + AI teams. 𝗪𝗮𝗻𝘁 𝘁𝗼 𝗹𝗲𝗮𝗿𝗻 𝗔𝗜? 𝗖𝗵𝗲𝗰𝗸 𝗼𝘂𝘁 𝘁𝗵𝗲 𝗳𝗿𝗲𝗲 𝗰𝗼𝘂𝗿𝘀𝗲𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀.👇🏻 Please ♻️ 𝗥𝗲𝗽𝗼𝘀𝘁 or 𝘀𝗵𝗮𝗿𝗲 so that others can learn too For high-quality resources on AI and Immigration, join my newsletter here https://lnkd.in/eBGib_va #AI #Leadership #FutureOfWork

What if upskilling your workforce on AI tools is making burnout worse, not better? New systematic review challenges conventional wisdom. A Cardiff University analysis of 201 studies (218,637 employees) reveals digital competence alone provides zero protection against technostress-induced burnout. Researchers identified two primary culprits destroying well-being: techno-overload (forced to work faster and longer through technology) and techno-invasion (constant connectivity bleeding into personal life). Sound familiar? The damage manifests as emotional exhaustion, burnout, and plummeting job satisfaction, even among highly digitally competent employees. 🔥 Why this matters for AI transformation leaders: Without organisational support structures in your AI rollout strategy, you're accelerating towards a well-being crisis. AI training increases digital capability but does nothing to protect psychological capacity. Sustainable transformation requires measuring technostress alongside adoption metrics. The question isn't "Can your people use AI?" It's "Can they use AI without breaking?" 💡 Evidence-based intervention strategies: → Organisational support trumps individual resilience. The meta-finding across 201 studies: training matters, but organisational support is the critical buffer. Give people permission, and systems, to disconnect. Make "strategic unavailability" a core value, not a career liability. Reward sustainable performance, not constant availability. → Diagnose technostress before it becomes burnout. Deploy validated diagnostic tools before and during digital transformations. Brief, single-item measures work brilliantly in fast-paced environments. You need real-time intelligence. → Target the actual stressors, not generic "wellness" The research is unambiguous: focus interventions specifically on techno-overload and techno-invasion. Different role types have different stressors. Create explicit digital boundaries (no-meeting blocks, async-first communication, mandatory shutdown protocols) modelled from leadership. 🧠 The organisations succeeding at AI adoption aren't just deploying the most sophisticated tools, they're protecting human capacity AND scaling digital capability. ---- 👋 Hi I'm Keith. I activate change and transform culture, leadership, and organisations, using behavioural science. Hit Follow for more on human-centred AI adoption strategies.

Rethinking Workforce Growth in the Age of AI AI “synthetic workers” are no longer a future concept. They are becoming a practical solution to real workforce challenges. In Jersey, leaders are now exploring how AI could expand the island’s workforce without increasing population, and the implications go far beyond one region. Here’s the context: Many economies are facing the same pressure: aging populations, limited housing, skills shortages, and rising labor costs. At the same time, demand for services keeps growing. Traditional hiring alone cannot solve this gap, and that is where AI-powered digital workers enter the picture. These systems are designed to handle routine, repeatable, and data-heavy tasks across finance, customer support, compliance, operations, and administration. They do not replace human judgment. They remove friction. What’s driving this shift: ✅ Businesses need to scale without expanding physical infrastructure ✅ Talent shortages are slowing growth in key sectors ✅ Remote and hybrid work models demand better digital support ✅ Productivity gains now matter more than headcount growth Instead of hiring for every new workload, organizations are using AI to absorb volume, standardize processes, and free teams to focus on higher-value work. The real opportunity is not cost-cutting. It is capacity. When digital workers handle the routine, human workers gain time for strategy, creativity, relationship building, and problem solving. That is how small regions, lean teams, and resource-constrained economies can compete at a global level. The question is no longer whether AI will reshape the workforce; it is how intentionally leaders choose to deploy it. Are synthetic workers part of your long-term workforce strategy? Let’s discuss. #ArtificialIntelligence #FutureOfWork #WorkforceInnovation #DigitalTransformation #AIinBusiness

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