Workflow Automation Hacks

I built an AI agent that handles my entire inbound system. (And I used to be against automation). Here's how I did it: I used two tools: --> Make: For automation workflows --> Relevance: For AI agents Here's what my AI agent handles: When someone fills our form, it- --> Analyzes their LinkedIn profile --> Reviews their website --> Checks if they match our criteria --> Makes a decision in seconds For qualified leads: --> Sends personalized pitch deck --> Books discovery calls --> Handles initial questions For non-qualified leads: --> Sends a thoughtful rejection --> Explains why we're not the right fit --> Keeps the door open for future The best part? My team and I can focus on what matters - strategy and client success - instead of spending hours on admin work. No more: -Manual lead checking -Back-and-forth emails -Calendar scheduling headaches -Just high-quality conversations with pre-qualified founders. Want to know the biggest lesson? Automation isn't about replacing the human touch. It's about creating more time for it.

𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝘀𝗰𝗮𝗹𝗶𝗻𝗴 𝗳𝗮𝘀𝘁 — 𝗕𝘂𝘁 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝘁𝗵𝗲𝘆’𝗿𝗲 𝗮 𝗠𝗔𝗦𝗦𝗜𝗩𝗘 𝗿𝗶𝘀𝗸! There’s a lot of buzz about how soon we’ll have millions or even billions of AI agents on the internet, reshaping businesses. If this becomes reality, a holistic security approach will become absolutely crucial. Below you can find an insightful breakdown from Accenture's Tech Vision 2025 on security considerations and best practices: This model highlights how enterprises must secure AI agents at every stage — from model development to human-agent interactions — ensuring resilience, governance and compliance. Let's break it down: 𝗦𝗲𝗰𝘂𝗿𝗶𝗻𝗴 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝘀 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗳𝗼𝘂𝗿 𝗸𝗲𝘆 𝗮𝗿𝗲𝗮𝘀: - Secured Identity & Access Management - Secured Workflow   - Secured AI Runtime   - Human in the Loop 𝗧𝗼𝗽 5 𝗯𝗲𝘀𝘁 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝗳𝗼𝗿 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆: 1. Zero Trust Security Model – Assume no implicit trust and verify every request as if it originates from an open network. This includes identity, device, and contextual verification.  2. Context-Aware Access – Dynamically adjust permissions based on real-time factors like location, device status and user behavior, reducing the attack surface.  3. Ephemeral Access – Use just-in-time permissions so AI agents only have access for the duration of their tasks, minimizing unauthorized access.  4. Lifecycle Management – Oversee the full lifecycle of AI agents: creation, modification, and de-provisioning, while continuously updating access controls.  5. Credential Management – Automate the rotation of credentials, keys, and certificates to reduce risk and eliminate human error.  You can find the full study here: https://lnkd.in/dP4RevKw

✨ Did You Know? ✨ You can now extend Dataverse using Low-Code Plug-ins with Power Fx—no C# required! 🙌 💡 With Low-Code Plug-ins you can: 🔹 Run custom business logic directly in Dataverse events (create, update, delete). 🔹 Use the same familiar Power Fx language from Canvas Apps and Model-driven Apps. 🔹 Combine with traditional plug-ins and Power Automate flows for advanced automation. 🔹 Ensure logic executes server-side for consistency and performance. ⚠️ But don’t forget: Check for other automations on the same event to avoid conflicts. Update only necessary columns to prevent triggering extra flows. Use pre-operation to avoid infinite loops when updating the same row. 👉 Low-Code Plug-ins bring the power of Power Fx into Dataverse automation, making it easier for both business users and pro devs to collaborate. Would you start replacing some of your lightweight code plug-ins with Power Fx? 🤔 https://lnkd.in/d4y3keXS #PowerPlatform #PowerFx #Dataverse #LowCode #Dynamics365

Hyperautomation has emerged as a game-changer in the technological landscape, changing how businesses streamline operations, reduce costs, and enhance efficiency. By combining AI, ML, and robotic process automation (RPA), it transformed industries. Gone are the days when automation was limited to assembly lines or customer service bots. Hyperautomation transforms everything — from crunching financial data to streamlining inventory management — into a unified, efficient digital ecosystem. For instance: ▶️ In warehouses, IoT devices monitor inventory and trigger restocking before shelves go empty ▶️ Financial tools like RPA bots process invoices while AI forecasts cash flow trends ▶️ ML algorithms pinpoint supply chain inefficiencies and suggest actionable fixes The result? A seamless, real-time operational flow that saves time, money, and resources. Gartner projects that by 2026, 30% of enterprises will automate more than half of their network activities- up from under 10% in 2023. In finance, AI algorithms detect fraudulent transactions faster than human analysts, while RPA tools manage expenses and generate reports in seconds. Customer service chatbots powered by natural language processing (NLP) handle routine queries, leaving human agents free to focus on high-stakes issues. In manufacturing, predictive maintenance minimizes costly machine downtime by identifying potential issues before they arise. AI-powered quality control systems catch product defects that human eyes might miss, while workflow automation optimizes resource allocation. In the ever-complex supply chain, hyperautomation ensures real-time responsiveness. AI systems analyze traffic and weather to optimize delivery routes, while IoT devices keep stock levels in check. The result? Faster deliveries, fewer errors, and significant cost savings. While the potential of hyperautomation is undeniable, it raises questions about its impact on human labor. Repetitive, low-skill jobs are at the highest risk of being replaced. But, this shift also opens doors for workers to upskill to manage and optimize these systems, focusing on creative and strategic tasks instead of mundane ones. The narrative shouldn’t be “man versus machine” but “man with machine.”  Valued at $45 billion in 2024, the hyperautomation market is projected to exceed $307 billion by 2037. Its future lies in driving sustainability, enabling hyper-personalized experiences, and achieving seamless end-to-end automation. As businesses continue to embrace this technology, it’s vital to maintain a human-centric approach: prioritizing ethical considerations, data privacy, and workforce training. The real question is: How will we harness its potential? #technology #AI #automation #innovation #business

My take on what's actually happening in automation right now: The gold rush is over. The reality check is here. What I'm seeing with clients: 👉 Less "we need AI!", more "we need this specific problem solved." 👉 Less shiny tools, more lean, strategic workflows.  👉 Less automation everywhere, more automation that matters. The shift is subtle but significant: Companies aren't asking for fancy tech. They're asking for smarter thinking about their processes. My prediction for 2025? The winners won't be the ones with the MOST automation. They'll be the ones with the most thoughtful automation. Smart companies are asking: 1️⃣ Which processes actually need automation? 2️⃣ Where are we automating around problems we should eliminate? 3️⃣ How do we measure automation success beyond time saved? We're finally moving past the "automate everything" hype cycle to something more valuable: Intentional automation. And that’s definitely reason to celebrate. What’s a shift you’re seeing in your industry? -- Hi, I’m Nathan Weill, a business process automation expert. ⚡️ At Flow Digital, we help business owners like you unlock the power of automation with customized solutions so you can run your business better, faster, and smarter. #automation #workflow #strategy #2025 #trends

SMBs are facing a critical challenge: how to maximize efficiency, connectivity, and communication without massive resources. The answer? Strategic AI implementation. Many small business owners tell me they're intimidated by AI. But the truth is you don't need to overhaul your entire operation overnight. The most successful AI adoptions I've seen follow these six straightforward steps: 1️⃣ Identify Immediate Needs: Look for quick wins where AI can make an immediate impact. Customer response automation is often the perfect starting point because it delivers instant value while freeing your team for higher-value work. 2️⃣ Choose User-Friendly Tools: The best AI solutions integrate seamlessly with your existing technology stack. Don't force your team to learn entirely new systems. Find tools that enhance what you're already using. 3️⃣ Start Small, Scale Gradually: Begin with focused implementations in 1-2 key areas. This builds confidence, demonstrates value, and creates organizational momentum before expanding. 4️⃣ Measure and Adjust Continuously: Set clear KPIs from the start. Monitor performance religiously and be ready to refine your AI configurations to optimize results. 5️⃣ Invest in Team Education: The most overlooked success factor? Proper training. When your team understands both the "how" and "why" behind AI tools, adoption rates soar. 6️⃣ Look Beyond Automation: While efficiency gains are valuable, the real competitive advantage comes from AI-driven insights. Let the technology reveal patterns in your business processes and customer behaviors that inform better strategic decisions. The bottom line: AI adoption doesn't require disruption. The most effective approaches complement your existing workflows, enabling incremental improvements that compound over time. What's been your experience implementing AI in your business? I'd love to hear what's working (or not) for you in the comments below. #SmallBusiness #AI #BusinessStrategy #DigitalTransformation

When most people hear automation, they think of expensive robots, complex integrations, and big enterprise budgets. It feels out of reach for smaller businesses. But it doesn’t have to be. Research from MIT Sloan School of Management shows that SMEs can approach automation differently, and affordably, without losing sight of competitiveness. One way is to start with peripheral processes. These aren’t the core operations that need high reliability, but the supporting activities that often drain time and attention. Think QR codes to monitor container unloading, sensors to track equipment health, or simple smartphone apps to give real-time visibility. Small steps like these can improve efficiency by 10–15% with minimal cost. Another way is to use stand-alone solutions. These don’t require deep IT integration, which makes them easier to deploy and scale. AI chatbots, IoT sensors, or plug-and-play analytics tools can be rolled out gradually, growing with the business rather than demanding heavy upfront investment. The lesson is simple: automation costs spiral when you chase customisation, tight integration, or unnecessary reliability. Costs come down when you design for compatibility, modularity, and just-enough functionality. For SMEs, the challenge isn’t whether automation is possible, but it’s learning where to start, and being smart about how far to go. Start small, scale at your own pace, and you’ll find automation doesn’t have to break the bank. #Automation #DigitalTransformation #SMEs #Innovation

The real challenge in automation isn’t just replacing manual tasks but creating an ecosystem where AI-driven efficiency enhances human decision-making, allowing businesses to scale smarter, personalize interactions, and free up talent for truly strategic initiatives. Hyperautomation leverages AI, robotic process automation (RPA), and predictive analytics to optimize operations, offering businesses a way to enhance efficiency while reducing costs. By automating communications through chatbots and virtual assistants, companies ensure customers receive instant, accurate responses, improving satisfaction and loyalty. Predictive insights enable firms to anticipate market trends and consumer behavior, driving proactive decision-making. Integrating multiple data sources into a unified system allows for smarter strategies, while real-time analysis ensures continuous process refinement. This shift transforms organizations from reactive to adaptive, fostering agility in an increasingly dynamic digital landscape. #AI #Hyperautomation #Automation #PredictiveAnalytics #DigitalTransformation

3 Salesforce automations tech companies should implement today (If they want to scale without the busywork): Manual tasks are killing your growth. If you’re still assigning leads, chasing follow-ups, or leaving renewals to chance - you’re moving too slow. Here’s how to fix it: 1) Automate lead assignment When a new lead comes in, speed matters. Don’t waste time manually routing leads to your team. Set up automation to assign leads instantly based on: • Territory • Deal size • Product interest Your reps should know exactly who owns the lead - the moment it enters the system. 2) Automate follow-up tasks Manual task creation is a silent time killer. Your CRM should automatically trigger follow-up tasks when: • A new lead is assigned • A deal moves stages • A prospect replies No more guessing. No more forgetting. Just clear next steps, every time. 3) Automate renewal reminders Retention is revenue. Your CRM should automatically flag upcoming renewals to your team, so nothing slips through the cracks. Better yet: • Trigger upsell tasks based on customer activity • Automate renewal workflows to keep deals moving Retention revenue is the fastest win for scaling tech companies. Your CRM should make it automatic. The more you automate, the more time your team spends on what matters: closing deals and keeping customers. Don’t let manual tasks slow you down. P.S: Subscribe to my newsletter — I share proven ways to turn your CRM into a growth engine. Sign up here: https://lnkd.in/gBukTtJN

Here's another way we're using AI at Reformed IT to improve our client experience without replacing the human touch 👇🏻 Every time a client emails us about an issue, we use AI to analyse the tone of their email and the likely level of satisfaction. 📩 Their tone could be: 🤬 Angry 😠 Frustrated 🤔 Confused 😟 Concerned 😐 Neutral 😊 Polite 😁 Happy Which would in turn lead to a likely satisfaction score between 1 - 10. If we detect that a client is Angry or frustrated with us based on their emails, we'll flag this ticket automatically with our head of service, Dan, to review. ✅ As you'll have seen recently, we track a lot of stats/data around customer service and satisfaction. 📊 However, we will only get feedback after we've completed a task. But we're picking up sentiment from the client during the entire interaction. By looking at the signs of frustration early on, we're more likely to be able to deal with the root cause of these frustrations and ensure that we turn it around to have a happy client by the time we've done the work. 😁 I've talked a lot about AI recently and the fact it will have an impact on jobs, but I also think, when used in the best way, it can really empower your business and people to do the best they can. 🤖 + 👨🏻💼 Are you using AI and Automation to improve your client experience? If so, how?