Balancing Technology With Work

Will Accounting Be Replaced? 🤖 💼 Everyone's asking if AI will replace accountants... Let me settle this once and for all. ➡️ WHAT WILL TRANSFORM ADVISORY SERVICES are becoming the heart of what we do. Gone are the days when accountants just crunch numbers. Now we guide strategic decisions using real data insights. Companies need advisors who understand both numbers AND business strategy. FORENSIC ACCOUNTING gets supercharged with advanced analytics. Finding fraud used to be like searching for a needle in a haystack... With AI-powered anomaly detection, we spot patterns humans would miss. The fraudsters are getting smarter, but so are our tools. AUDIT & RISK ASSESSMENT will never go away, but everything about it is changing. Instead of sampling transactions once a year, we're moving to continuous auditing with real-time data. AI review systems flag issues as they happen, not months later when it's too late. FINANCIAL ANALYSIS & FORECASTING is where accountants shine brightest. Sure, AI can run calculations, but humans bring context to numbers. Our forecasting is getting enhanced by predictive analytics and scenario modeling that processes variables faster than ever before. CLIENT COMMUNICATION is shifting completely. We're moving from transaction processors to trusted advisors. ➡️ WHAT WILL BE REPLACED Let's be honest... some parts of accounting are tedious and perfect for automation. MANUAL DATA ENTRY is already on its way out. AI-driven data capture and OCR tools process invoices and receipts in seconds, without the errors humans make after hours of monotonous work. ROUTINE BOOKKEEPING tasks are getting automated through cloud accounting software. Bank feeds, automatic categorization, and machine learning mean the days of manually reconciling every transaction are numbered. BASIC TAX PREPARATION for standard situations will be handled by smart platforms. E-filing tools get smarter every tax season. The complex tax strategy work? That's still all us. INVOICE MATCHING & RECONCILIATION is perfect for automation. AI bots can match thousands of invoices to purchase orders in minutes, with real-time reconciliation systems keeping everything in sync. COMPLIANCE MONITORING no longer needs accountants to manually check every rule. Automated alerts and built-in compliance checks flag issues instantly, letting us focus on solving problems rather than finding them. ➡️ THE FUTURE ACCOUNTANT The accountants who will thrive aren't fighting against technology... They're embracing it. The future belongs to those who combine technical accounting knowledge with: - Strategic thinking - Business acumen - Technology fluency - Communication skills === What parts of your accounting job do you think will change the most with AI? Which skills are you developing to stay ahead? Join the discussion in the comments below 👇

Clinicians like me can interact with AI in two fundamentally different ways. In one paradigm, AI generates output for us to review and verify. In the other, we do the work and AI checks it for us. Both models have value. But the key is choosing the right one for the task at hand. That choice depends on several factors, including the clinician's capabilities, their preferences, and the reliability of the AI output. When I’m reviewing records or drafting (straightforward) notes, I often want AI to go first — I’ll check its work. But when I’m making decisions or replying to patient messages, I want to lead — and have AI check me. When those roles are mismatched, AI becomes a burden instead of a help. Here’s a non-clinical example, since (unlike EHRs) I can share the image below: I almost never use Copilot to draft emails. Yet every time I open a message, Copilot auto-suggests a few replies, unnecessarily taking up screen space and interrupting my flow. It’s the wrong paradigm, forced into the wrong moment. Stop showing it to me, please. Conversely, what stood out to me in the recent Penda Health / OpenAI study was how the AI reduced errors by %13-16% withOUT inserting itself into every clinical encounter. Instead of continually intruding onto the EHR screen, it operated more like a background safety net — surfacing only when it mattered. More health tech should be designed with that kind of discernment — and less like Copilot emails, intrusively barging onto our screens and into our minds whether useful or not. It's not just about what AI can do, but whether — and when — it should show up at all.

𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗶𝗻 𝘁𝗵𝗲 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱, 𝗖𝗿𝗮𝗳𝘁 𝗮𝗻𝗱 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗙𝗼𝗿𝗲𝗴𝗿𝗼𝘂𝗻𝗱 I still remember those endless nights in SEPHORA, manually counting thousands of items. That’s why Starbucks’ announcement today resonated so strongly with me. They are rolling out AI-powered automated counting across all their North America coffeehouses: 11k stores. What’s remarkable is the technology mix: 👀 Computer vision to instantly recognize products on shelves. 🔢 3D spatial intelligence to capture placement and quantities. 🪩 Augmented reality overlays guiding partners through the process. 📈 AI analytics that flag low-stock items and will soon automate replenishment orders. The results are striking: ✅ Inventory now counted 8x more frequently. ✅ A process that used to take one hour, now takes minutes. They are reporting a saving of 16,500 hours per week. ✅ Sales people spend less time in the backroom and more time crafting and connecting with customers. Starbucks calls it “technology in the background, craft and connection in the foreground”. And that’s exactly why it matters: technology here is the enabler of efficiency, consistency, and focus on consumer experience. Starbucks is not alone. Walmart with robots scanning shelves, Inditex embedding RFID across its stores, and Amazon Go pioneering frictionless checkout all point to the same truth: the future of retail advantage lies in mastering the invisible backbone of operations. 👉 We’ve moved beyond pilots and “experiments.” AI, AR and computer vision are becoming part of operational infrastructure. Having lived both sides, the manual counts and the promise of automation, I guess this will become the standard for every retailer. #RetailInnovation #AI #AugmentedReality #Operations #CustomerExperience

#Physicians aren’t resisting #AI. They’re resisting being erased from the conversation. Every week, I hear the same thing from colleagues. We’re using AI. We see the value. But we weren’t asked how it should show up in our clinical lives. The data makes that disconnect impossible to ignore: • 67% of physicians already use AI daily • 84% say AI makes them better at their jobs • 81% are dissatisfied with how their organizations deploy it • 71% report little or no influence over AI decisions So the issue isn’t adoption. It’s agency. From the front lines, what clinicians actually want is simple: • Less documentation — not new layers to review • Fewer clicks — not more dashboards • Time back for patients — not metrics for administrators And what they’re pushing back against is just as clear: • AI imposed top-down without clinical input • Tools optimized for billing and payers, not care • Responsibility and liability without protection or transparency This is the part that often gets missed. AI doesn’t fail in healthcare because doctors resist change. It fails when doctors are treated as end-users instead of co-designers. Technology should augment clinical judgment not sideline it. If healthcare AI is going to earn trust, it won’t be because the algorithm is smarter. It’ll be because clinicians were given a real seat at the table. What would change in your organization if physicians helped shape AI from day one? #HealthcareAI #PhysicianLedAI #HumanInTheLoop #DigitalHealth #DrGPT

Clinicians don’t trust your HealthTech product. And they’re right not to. You think you’re selling innovation. But they’re seeing liability. When a doctor uses your product, they’re not just clicking a button. They’re staking their license, reputation, and someone’s life on a tool they didn’t build… Made by someone who’s never stepped inside an operating theatre. This is the Clinical Trust Chasm. Most HealthTech companies never cross it. They win pilots, not trust. Investors, not integration. Press, not protocols. Trust in medicine isn’t earned with features. It’s earned with consequences. Ask any surgeon why they use a specific tool. It’s not because it’s cutting-edge. It’s because it’s predictable under pressure. They’ve seen it fail, and seen what happens next. They know it's blind spots. They know when not to use it. You can’t shortcut that with UI polish and a few endorsements. If you want your HealthTech product to be adopted, not just trialled: You have to reverse the trust equation. Here’s how I’ve seen it work: - Put the clinician in control - Stop “automating decisions”. Start augmenting judgement. - Build fail-safes, override paths, audit trails. Trust starts when you acknowledge what you don’t know. Design for blame Assume someone will get hurt using your product. Will they say: “We knew this tool. We trusted it. We stood by it.” Or: “They promised it would work.” Over-communicate uncertainty No one’s ever said, “That medical device was too transparent.” Show the confidence intervals. Flag the edge cases. Clinicians are trained to work with ambiguity, just not surprise. Many HealthTech founders think clinicians are “resistant to change”. IMO they’re not. They’re allergic to risk they didn’t consent to. They don’t need to understand your model. They need to understand how it breaks, and what happens when it does. Build for that moment. That’s where real adoption begins.

AI isn’t a shift in the quality of care, it’s a shift in the practice of it. As clinicians, we’ve always been committed to delivering quality care. That commitment isn’t new. What’s evolving, what’s disruptive, is how we practice. How we document, decide, and deliver. How we connect with patients and with one another.   AI is threading itself into our workflows in subtle and not-so-subtle ways. From ambient scribing and diagnostic models to clinical decision support, care navigation, and patient communication, AI is either being considered or implemented. These are not just time-saving tools. They’re behavior-shaping technologies.   That means this moment is about more than adoption. It’s about transformation. I don't use that word lightly. We can't improve upon what is broken; we have to revolutionize our approach. In my role as Vice Chair for Innovation and Professor at the University of Pittsburgh School of Health and Rehabilitation Sciences , I spend a lot of time speaking with clinicians, health systems, and tech leaders. And I keep emphasizing that clinicians must be co-architects of this transformation.   Too often, AI solutions are deployed without enough input from those who understand the nuance of patient care. That gap can lead to tools that promise efficiency but disrupt workflows or worse, tools that inadvertently erode trust and connection. We don’t need more tech for tech’s sake. We need tech that enhances human care. That’s why I encourage health systems and innovators to bring clinicians in early and often. When we lead the design process, we can build systems that amplify insight, reduce burnout, and preserve the empathy at the heart of healthcare.   Here’s the lens I encourage my students, colleagues, and collaborators to adopt: -AI should augment, not automate, clinical thinking -Design should be human-first, not backend-first -Clinicians should be at the table, not just in the training module   The future of medicine isn't just algorithmic; it's collaborative. The clinician’s role is not disappearing; it’s evolving. And we have the opportunity and responsibility to shape what that evolution looks like. I'm honored to lead through the University of Pittsburgh School of Health and Rehabilitation Sciences to spark meaningful conversations about the future of care, the role of clinicians in digital transformation, and the ethical deployment of AI in practice.   Let’s not be passive recipients of change. Let’s be purposeful designers of it. If you’re building, leading, teaching, or innovating in this space, I’d love to connect. Because I think when clinicians lead, AI doesn’t replace us. It reveals the best of us.  

The future of accounting isn't replacement. It's transformation. Basis just raised $34M to build AI agents for accountants. A signal of the shift happening in professional services. Here's what's changing today: → Weeks of work done in minutes → Analysis becomes continuous → Real-time error detection → Proactive compliance But core value evolves: → Assurance grows in importance → Pattern recognition becomes key → Cross-border complexity rises → Strategic guidance matters more The winners won't be who you expect: → Not the largest firms → Not those with most staff → Not even those with biggest budgets It will be those who understand: → AI augments judgment, not replaces it → Small teams can match big firm output → Quality scales differently with technology → Expertise matters more than ever The moat of scale that protected the Big 4 is evaporating. Soon, the best firms won't be measured by their headcount. But by their ability to deliver intelligence at scale.

𝐒𝐭𝐚𝐫𝐛𝐮𝐜𝐤𝐬’ 𝐑𝐞𝐯𝐢𝐯𝐚𝐥: 𝐖𝐡𝐲 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞, 𝐍𝐨𝐭 𝐉𝐮𝐬𝐭 𝐂𝐨𝐟𝐟𝐞𝐞, 𝐈𝐬 𝐈𝐭𝐬 𝐍𝐞𝐰 𝐆𝐫𝐨𝐰𝐭𝐡 𝐄𝐧𝐠𝐢𝐧𝐞 For decades, Starbucks has been more than a coffee chain. It’s been a Third Place—a cultural touchpoint between home and work, where people gathered, connected, and belonged. But somewhere along the way, Starbucks lost its soul. In the chase for efficiency, speed, and automation, many stores became transactional hubs instead of experiential destinations. Customers rushed in, grabbed their latte, and left—missing the warmth that once defined the brand. ✳️By 2024, the cracks were visible: 6–7% drop in sales across U.S. and global markets. Declining foot traffic as faster, cheaper rivals gained ground. A growing perception of Starbucks as impersonal and “soulless.” Even loyal customers admitted the “magic” was gone. Now, under CEO Brian Niccol, Starbucks is hitting reset with its Back to Starbucks 2025 strategy—a revival focused not on discounts or gimmicks, but on human experience. ✳️The Comeback Playbook Redesign Cafés → Cozy seating zones, ceramic mugs, condiment bars. Stores that invite people to stay, not just sip and leave. Retrain Baristas → Through the “Green Apron Service Model,” employees are encouraged to prioritize warmth and hospitality over mere speed. Balance Tech + Touch → Mobile ordering stays, but as support—not a replacement—for in-store connection. Simplify the Menu → Less clutter, more focus on core coffee, seasonal favorites, and premium brews. Even pricing is being reset with no upcharges for non-dairy options. ✳️Why This Matters for Retail This isn’t just Starbucks’ story. It’s a reminder for every brand: products can be copied, but experiences cannot. In an age of e-commerce, physical spaces win only if they engage the senses, foster belonging, and create emotional resonance. Starbucks’ revival is about making cafés feel like living rooms again. It’s not just selling coffee—it’s selling moments of connection, ritual, and community. ☕ Experience is the new strategy. Coffee is just the medium. To read the rest, visit link in comments

We keep saying AI will revolutionise healthcare. But what if the revolution is human-first? After years advising HealthTech founders, I’ve noticed a pattern: The technology is rarely the barrier. Adoption is. You can have the smartest algorithms in the world, but if clinicians don’t trust them, or patients don’t feel seen by them, the system fails. AI can process data at unimaginable speed. What it can’t do — yet — is deliver empathy, context, or care. And that’s where the next generation of founders must focus: designing intelligence that augments humans, not replaces them. The MIT × Roche report on scaling integrated digital health highlighted something profound, the companies that succeed aren’t the most technical. They’re the most collaborative. They design with clinicians, listen to regulators, and test in real-world care environments. In other words: they build trust before traction. I saw this firsthand when supporting a digital wellness platform. Their AI could detect emotional cues in voice patterns, but what won enterprise clients wasn’t the accuracy, it was the empathy in the experience. The tech didn’t talk at people; it talked with them. Healthcare is still, at its core, a human relationship. If we want AI to transform outcomes, we must embed humanity into its code: transparency, explainability, accountability. Technology should extend clinicians’ capacity for compassion, not erode it. The real future of digital health won’t be machines replacing medicine; it’ll be humans, enhanced by design. How do we make sure AI in healthcare stays human-centred, built for trust, not just efficiency? I’d love to hear how your company approaches that balance.

Zero-trust security killed our performance metrics. Until it didn't. How I built a security system that protects 2.1M daily telemetry events without slowing down. The board was worried. We needed tight security. But our 500ms speed couldn't suffer. So I focused on finding a design that wouldn’t force a trade-off between compliance and speed. I combined three Azure tools: → Fabric Real-Time Intelligence → Purview for governance → OneLake Catalog for control The magic happened when I: Auto-masked sensitive data across 22 tables. Protected all PII in JSON fields. Used in-memory processing to maintain speed. Preserved full data lineage for compliance. I tested three different approaches. Most added lag. But this combination was different. The results shocked everyone: Sub-second latency maintained. Full zero-trust compliance achieved. Even the board was impressed. Performance actually improved. The truth most security experts miss: Zero-trust doesn't mean zero-speed. You can have bulletproof security and lightning-fast performance. You just need the right architecture. What's your biggest challenge when balancing security and speed? Drop your thoughts below.