World of Workato: AI and Automation in Enterprise

On Tuesday I joined the AI2Elevate × Miro “𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐅𝐚𝐬𝐭𝐞𝐫 𝐢𝐧 𝐚𝐧 𝐀𝐈-𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞𝐝 𝐖𝐨𝐫𝐥𝐝” meetup — with 𝐀𝐧𝐝𝐫𝐞𝐲 𝐊𝐡𝐮𝐬𝐢𝐝 (Co-Founder & CEO, Miro), 𝐓𝐨𝐦á𝐬 𝐃𝐨𝐬𝐭𝐚𝐥 𝐅𝐫𝐞𝐢𝐫𝐞, 𝐁𝐫𝐚𝐦 𝐉𝐨𝐧𝐤𝐞𝐫, 𝐉𝐞𝐥𝐥𝐞 𝐒𝐜𝐡𝐨𝐞𝐧𝐦𝐚𝐤𝐞𝐫 (Tech CEO & Growth Architect), and 𝐂𝐥𝐚𝐮𝐝𝐢𝐚 𝐁𝐚𝐢𝐣𝐞𝐧𝐬 (VP of Product, TestGorilla). With Miro serving 90M users at 250K companies worldwide, it was great to hear the conversation first-hand. 𝐓𝐡𝐫𝐞𝐞 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝐈 𝐤𝐞𝐞𝐩 𝐡𝐞𝐚𝐫𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐡𝐞𝐚𝐫𝐝 𝐚𝐠𝐚𝐢𝐧 𝐨𝐧 𝐓𝐮𝐞𝐬𝐝𝐚𝐲: 💡 Agents & automation. AI (especially agent systems) can already automate a lot. 𝐓𝐡𝐞 𝐫𝐞𝐚𝐥 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐧𝐨𝐰 𝐢𝐬 𝐩𝐢𝐜𝐤𝐢𝐧𝐠 𝐚 𝐟𝐨𝐜𝐮𝐬 𝐚𝐧𝐝 𝐚 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐩𝐨𝐢𝐧𝐭: 𝐰𝐡𝐚𝐭 𝐭𝐨 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐟𝐢𝐫𝐬𝐭, so you get outcomes, not another “pilot for the sake of a pilot.” 💡 It’s not “AI replaces jobs,” it’s 𝐩𝐞𝐨𝐩𝐥𝐞-𝐰𝐢𝐭𝐡-𝐀𝐈 𝐫𝐞𝐩𝐥𝐚𝐜𝐞 𝐩𝐞𝐨𝐩𝐥𝐞-𝐰𝐢𝐭𝐡𝐨𝐮𝐭-𝐀𝐈. As Miro’s founder put it, specialists who use AI will outperform those doing manual, paper-heavy work. That’s where the shift is happening. 💡 𝐓𝐡𝐞 𝐛𝐢𝐠𝐠𝐞𝐬𝐭 𝐫𝐢𝐬𝐤 𝐢𝐬𝐧’𝐭 𝐡𝐚𝐥𝐥𝐮𝐜𝐢𝐧𝐚𝐭𝐢𝐨𝐧𝐬 — 𝐢𝐭’𝐬 𝐝𝐚𝐭𝐚. You have to know where the data comes from, how fresh it is, and how sources are managed. If data is noisy or fragmented, AI just scales the problem. Against that backdrop, the latest 𝐃𝐞𝐥𝐨𝐢𝐭𝐭𝐞’𝐬 𝐇𝐑 𝐑𝐞𝐢𝐦𝐚𝐠𝐢𝐧𝐞𝐝 paper lands at exactly the right moment: 𝐢𝐭’𝐬 𝐧𝐨𝐭 𝐚𝐛𝐨𝐮𝐭 “𝐨𝐧𝐞 𝐦𝐨𝐫𝐞 𝐟𝐞𝐚𝐭𝐮𝐫𝐞,” 𝐢𝐭’𝐬 𝐚𝐛𝐨𝐮𝐭 𝐡𝐨𝐰 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐫𝐞𝐰𝐢𝐫𝐞𝐬 𝐭𝐡𝐞 𝐥𝐨𝐠𝐢𝐜 𝐨𝐟 𝐇𝐑. I𝐈 𝐫𝐞𝐚𝐝 𝐭𝐡𝐞 𝐫𝐞𝐩𝐨𝐫𝐭 𝐚𝐧𝐝 𝐰𝐫𝐨𝐭𝐞 𝐚 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐠𝐮𝐢𝐝𝐞 — “𝐑𝐞𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐃𝐞𝐥𝐨𝐢𝐭𝐭𝐞’𝐬 𝐇𝐑 𝐑𝐞𝐢𝐦𝐚𝐠𝐢𝐧𝐞𝐝 𝐟𝐨𝐫 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐰𝐢𝐭𝐡 𝐑𝐚𝐢𝐥𝐫𝐨𝐚𝐝 𝐆𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬”, covering where AI already works, the risks to watch, and how to put guardrails in place so speed doesn’t break trust. 👉 Link to my article is in the first comment. Happy to compare notes on first steps and real-world pilots. #HR #HRLeadership #AgenticAI #HRTransformation #TrustByDesign #PeopleOps

📢 “Let’s become a hybrid organization.” — a what??? Some time ago, this is how I kicked off a change initiative at Easy Software Ltd. My opening slide? A hopefully funny image generated by AI—an icebreaker before introducing a serious goal: shifting from “AI as a tool” to “AI as a teammate.” AI wasn’t new to us. We had already made it part of our product, and many teams were using AI tools. But adoption ≠ culture. We didn’t want “everyone to use AI for everything.” We wanted people-led innovation, with AI & automation as the co-pilot. 🎯 The approach? - Listen first. Leadership can name critical processes; only teams can describe daily friction. - Focus on what people need—and what bothers them. Any change needs people buy-in: making their work better is a good approach, making it easier, is even better. - AI Canvas workshops for every team - to map team needs, limitations, and opportunities. - Show practical ways to ease work, not abstract promises. - Top-down + bottom-up. While we redesigned key processes, we invited teams to shape their own automations. 💥 What happened? - A prioritized backlog of meaningful ideas appeared in just a few weeks. - Champions emerged across teams—once they got the spark and the space, they started innovating on their own. - People were actually happier—not right away, of course, but once we rolled out automations in every team, manual processes stopped being a headache. People started having more time for what they do best (and enjoy). 💡 My takeaway: AI, automations, agents, digital workflows—these are means, not ends. The real unlock is engagement, proactivity, and honesty. When that’s in the culture, ideas compound. 👉 That’s how we became a hybrid organization: people + processes + digital teammates working in sync, with humans in the loop. Curious about the AI Canvas we used? 👇 Comment CANVAS and I’ll share the template. #Operations #COO #DigitalTransformation #AI #Automation #ChangeManagement #HybridOrganization

🚀 Reinventing Software in the Age of AI 📖 Deloitte’s new report “Reinventing the Future of Software in the Age of AI” shows one big truth: 💡 The software industry is facing its biggest platform shift since SaaS — and this time, AI is at the core. ⚡ This isn’t about just adding AI features. It’s about dual reinvention: 1️⃣ Embedding AI into products → 🚀 better user experience & new revenue streams 2️⃣ Embedding AI into the organization → ⚙️ streamlined development, 🤖 automation, 👩💻 reshaped workforce roles 📊 Key insights: ✨ Nearly 70% of SaaS companies with AI are already testing or monetizing features 🔄 Traditional software models → shifting to AI-native, self-optimizing systems 🏆 Leaders will move from incremental adoption → to full AI reinvention (pricing, GTM, workforce) 🔐 Success depends not only on speed, but also on trustworthy, explainable, outcome-driven AI 🎯 Treat AI as a strategic priority — those who move first could redefine the industry 🌍 The message is clear: We’re not just in another SaaS wave… AI is rewriting the entire software playbook. #AI #Software #SaaS #DigitalTransformation #Innovation #FutureOfWork

*Part 3 - Why 95% of Enterprise GenAI Projects Fail: Structural Traps Enterprises Fall Into* As we proceed with breaking down MIT’s study, the research as observed interesting phenomena - *Flashy over Focus* -Companies overspend on flashy sales & marketing pilots, while back office automation (often with higher ROI) gets ignored.  - Scale Drag – Large firms run more pilots but scale slower 9 months on common vs. 90 days for mid size companies.  - *Industry Divide* - Only tech and media show real impact; other industries remain stuck in experimentation.  - *Spiritless Funnel* - Out of all tools evaluated, only 20% make it to pilot, and just 5% reach production with measurable impact. Overall, the entire cycle is very costly, involving numerous experiments with little measurable value. Which led me to an understanding that Success isn’t about more pilots. It’s about choosing the right ones, aligning to ROI, and building integration muscle. ❓ Question: If you had to bet on one business area where GenAI could actually deliver ROI in your org, where would it be? #GenAI #AI #Innovation #AIAdoption #MITResearch

#𝗙𝗿𝗶𝗱𝗮𝘆𝗟𝗲𝗻𝘀 – 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝗙𝗼𝗿𝘄𝗮𝗿𝗱 #𝟭𝟯 AI LEADERSHIFT : FROM ORG CHART TO WORK CHART For over a century, we’ve organized work around 𝘁𝗶𝘁𝗹𝗲𝘀, 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗹𝗶𝗻𝗲𝘀, 𝗮𝗻𝗱 𝗵𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝘆. That’s the 𝗼𝗿𝗴 𝗰𝗵𝗮𝗿𝘁: a map of control. But today, something new is emerging. AI is not just supporting our work — it’s 𝗱𝗼𝗶𝗻𝗴 the work: Writing code, Analyzing data, Scheduling meetings, Designing slides, Quietly, Consistently, Invisibly. And yet, our charts don’t reflect this. What if we stopped asking "𝘞𝘩𝘰 𝘳𝘦𝘱𝘰𝘳𝘵𝘴 𝘵𝘰 𝘸𝘩𝘰𝘮?" And started asking "𝘞𝘩𝘰 𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘴 𝘸𝘩𝘢𝘵 𝘷𝘢𝘭𝘶𝘦?" That’s the 𝘄𝗼𝗿𝗸 𝗰𝗵𝗮𝗿𝘁. A map of 𝗮𝗰𝘁𝗶𝗼𝗻, 𝗳𝗹𝗼𝘄, 𝗮𝗻𝗱 𝘀𝗵𝗮𝗿𝗲𝗱 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀 — where humans and AI agents collaborate in real time. It doesn’t care about job titles. It cares about 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀, 𝗵𝗮𝗻𝗱𝗼𝗳𝗳𝘀, 𝗮𝗻𝗱 𝗿𝗲𝘀𝘂𝗹𝘁𝘀. Leading organizations are already making the shift: -->𝙈𝙞𝙘𝙧𝙤𝙨𝙤𝙛𝙩 is moving toward “agentic societies” by embedding AI into core teams #CoreAI (https://lnkd.in/eZ-Zgcjg) -->𝙎𝙚𝙧𝙫𝙞𝙘𝙚𝙉𝙤𝙬, 𝙎𝘼𝙋, 𝙖𝙣𝙙 𝙞2𝙘 deploy AI agents to handle workflows and customer operations ( https://lnkd.in/ehYXRj48) -->𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀 𝗹𝗶𝗸𝗲 𝗔𝗿𝘁𝗶𝘀𝗮𝗻 𝗔𝗜 and Moveworks are branding their tools as “digital colleagues” (https://lnkd.in/eFyAiYYk) They’re not replacing people. They’re 𝗿𝗲𝗱𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝘄𝗼𝗿𝗸. The org chart was built for control. The work chart is built for 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 — 𝗵𝘂𝗺𝗮𝗻 + 𝗔𝗜, side by side. One is rigid. The other is 𝗱𝘆𝗻𝗮𝗺𝗶𝗰, 𝗮𝗱𝗮𝗽𝘁𝗶𝘃𝗲, 𝗮𝗻𝗱 𝗮𝗹𝗶𝘃𝗲. This is not just digital transformation. It’s organizational transformation. And if we’re honest — Some of our org charts are just illusions of order Hiding the real chaos underneath. Let’s redraw them. Let’s 𝗯𝘂𝗶𝗹𝗱 𝗳𝗼𝗿 𝗳𝗹𝗼𝘄, 𝗻𝗼𝘁 𝗳𝗼𝗿𝗺. Let’s co-design the future of work — together. 𝗛𝗮𝘃𝗲 𝗮 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹 𝘄𝗲𝗲𝗸𝗲𝗻𝗱! #AILeaderShift #OrganizationalDesign #AgenticWork #FutureOfWork #AfricaBuilds

Day-to-Day Productivity Boost with AI I recently attended an insightful session as part of the Be10X AI Career Accelerator – Inner Circle, where we explored how AI can transform our daily workflows and help us reclaim valuable time. 💡 Key Takeaways: Automating repetitive tasks can save up to 40% of your workday. AI tools in task management, scheduling, writing, meetings, and workflow automation let you focus on high-value, creative work. From tools like Notion, Coda, Reclaim AI, Integrately, Compose AI, Otter.ai, Fireflies AI, and InVideo, each plays a role in making work more efficient and stress-free. The true power of AI is not in replacing us, but in empowering us to innovate and focus on strategic thinking. ✨ My biggest insight: Productivity isn’t about working harder—it’s about working smarter with AI. 🔜 Excited to start applying these tools in my workflow and see how much time I can reclaim! #AI #Productivity #Be10X #Automation #ArtificialIntelligence #CareerGrowth

Confession: I used to think automation was a job only for hardcore coders and technical wizards. The thought of building AI-driven workflows always seemed intimidating—until recently. Today, low-code/no-code AI platforms like FlowForma’s [AI Copilot](https://lnkd.in/gxPi5sN7), Zapier ([see here](https://lnkd.in/g6QFmiQP)), and Blaze.tech ([details here](https://lnkd.in/g-TuEAGG)) are democratizing complex automation. These tools combine drag-and-drop simplicity with powerful AI to help even senior leaders and SMB owners automate multi-step processes without wrestling with code. Integration with thousands of apps is standard, and specialized solutions now serve compliance-heavy businesses securely. In my own work, leveraging no-code tools layered with generative AI has revolutionized how we design client workflows. For example, by integrating AI document processing engines like Levity AI ([source](https://lnkd.in/gMSHqntq)) into routine sales tracking, we cut manual touchpoints by 40%, boosting both accuracy and throughput—all built without writing a single line of code. What’s exciting to me is how these platforms create space for any professional to experiment, innovate, and optimize. If you’ve been hesitant about diving into AI automation, I encourage you to try a tool like Zapier or FlowForma’s Copilot. Start small, then watch how rapid iteration empowers your team’s productivity. How have you or your organization tapped into low-code/no-code AI tools? What successes or challenges have stood out? I’d love to hear your experience—drop a comment or send me a DM. And if you’re curious about practical ways to start your AI workflow journey, feel free to follow for tips and real-world case studies. #Automation, #ArtificialIntelligence, #LowCodeNoCode, #DigitalTransformation, #WorkflowAutomation, #NoCodeAI, #AIAutomation, #BusinessProductivity, #SMBTech, #AIWorkflow, #AIChatGPT, #FutureOfWork

Many leaders are asking how to actually implement AI beyond basic chatbots. A vague strategy isn't enough. I came across this step-by-step guide from Salesforce on becoming an "Agentic Enterprise," and it's one of the most practical frameworks I've seen. It breaks down the journey into manageable stages, starting with choosing the right "quick win" use case to build momentum. Key takeaways for me: Start with Vision, Not Tech: Define the business capability you want to scale before choosing a tool. Prepare Your People: Success is less about technology and more about change management and preparing your team for human-AI collaboration. Data is Your Foundation: Your AI is only as good as the data it's grounded in. If you're looking for a roadmap that goes beyond theory, this is worth your time. #AIImplementation #DigitalStrategy #ChangeManagement #FutureOfWork #AgenticAI #BusinessGrowth

I know you (incl me:)) are getting ready for the long weekend and I want to be generous in keeping my posts short but yet compelling. This week I read various articles including from none other than Sam Altman, that AI is in a hype cycle. When this happens, executives are in a dilemma. Do you take the bait and join the bandwagon with FOMO or do you run the risk of being a laggard? Fortunately, there's a middle path. We’re in peak AI hype. Everyone wants to “flip the switch” and watch magic happen. Yet MIT’s State of AI in Business 2025 shows 95% of AI agent pilots never scale. Not because the tech fails, but because companies jump in without answering the most important question: Why? Simon Sinek reminds us: Start with Why. If your “why” is only FOMO, the program will stall. If your “why” is solving a real tangible business problem like SLA breaches, refund delays or ticket backlogs , NowAssist becomes a strategic co-pilot, not a novelty. Best Practices That Stick 1. Start with One High-Value Use Case Pick a burning workflow (password resets, returns, onboarding). Early wins earn trust and credibility. 👉 Gartner predicts by 2026, 80% of enterprises will operationalize AI only for high-value workflows. 2. Anchor Reporting in Outcomes Executives don’t care about “sessions handled.” They care about dollars saved, risks reduced and CSAT lifted. Tie $ucce$$ metrics to those. 3. Design for the Human in the Loop Keep critical flows deterministic (refunds, compliance) while using GenAI for intent and summarization. Trust is everything. 4. Make Change Management a Feature Train, communicate, celebrate wins. McKinsey finds companies that invest in change management see 3.5x more impact. 5. Crawl → Walk → Run Crawl: FAQs & common requests Walk: Multi-step workflows Run: Predictive, proactive insights #NowAssist #AI #Work4Flow #ServiceNow

🛠 Most AI Implementations Fail Because Companies Skip These 6 Critical Phases Here's the brutal truth: 70% of AI projects never make it to production. The reason? No systematic implementation process. At MindWaves AI, we've cracked the code with our battle-tested 6-Phase methodology that turns AI promises into measurable business results. 🔍 PHASE 1: Deep Discovery & Systems Analysis We audit your data infrastructure, workflows, and bottlenecks with forensic precision. No assumptions, no shortcuts—just actionable intelligence that drives every decision. 🎯 PHASE 2: Custom Strategy & AI Architecture Design Your business gets a bespoke AI solution designed for your specific challenges and opportunities. Zero cookie-cutter approaches, maximum competitive advantage. ⚡️ PHASE 3: Agile Development & Rigorous Testing Rapid build cycles with continuous validation. Every feature tested against real-world scenarios before it touches your operations. 🔗 PHASE 4: Seamless Integration & Zero-Downtime Deployment Your existing systems stay operational while AI capabilities integrate smoothly. Business continuity guaranteed, productivity immediately enhanced. 🎓 PHASE 5: Team Enablement & Adoption Acceleration Your people become AI-powered from day one. Comprehensive training that turns skeptics into champions and users into power users. 📈 PHASE 6: Continuous Optimization & Performance Monitoring Real-time performance tracking, proactive adjustments, and ongoing refinement as your business scales and evolves. 💡 The MindWaves Difference: ✅️ Complete transparency - You see every step, every decision, every result ✅️ Risk elimination - Defined success metrics and rollback protocols ✅️ ROI acceleration - Measurable impact within 90 days of deployment ✅️ Future-proofing - Scalable architecture that grows with your business The companies winning with AI aren't just buying technology—they're following proven implementation methodologies. Which phase of AI implementation is your biggest concern? Drop a comment and let us know where you need the most clarity. We'll share specific insights from our experience with similar implementations. Your AI transformation success starts with trusting the process, not just the technology. #AIImplementation #DigitalTransformation #ProcessOptimization #AIStrategy #BusinessAutomation #MindWavesAI