Smart Technology Adoption

Most Entrepreneurs Think Leadership Is About Having All the Answers: (Here's What Actually Drives Results) Great vision might inspire your team. But Empowering smart people gets you breakthrough solutions. Yet most entrepreneurs get stuck… → Micromanaging every decision instead of trusting their team → Missing opportunities due to lack of adopting new technologies → Spending all their time in meetings instead of enabling action Let's be real: After building 7 companies and generating $800M+ in eCommerce, I've learned this: The best leaders create environments where innovation happens naturally. Here's what happened last week: My team was frustrated. Client proposals were taking forever because we needed custom market size calculations for every pitch. Instead of telling them "just use Excel" or "we'll hire developers eventually," I said: "Figure it out. Use whatever tools you need." Two hours later, they had a solution. One of my team members discovered 'Emergent' → An agentic platform that builds production-ready apps from natural language. They simply said: "Build a market size calculator for client proposals", and also added necessary details. Minutes later, we had a production-ready application that: → Processes demographic data and pricing models automatically → Applies market sizing formulas with demographic analysis → Generates revenue projections and investor-ready reports → Shows all assumptions transparently for client confidence → Cost us under $20 in AI credits to build This is what happens when you trust smart people with smart tools. While other leaders are still debating AI adoption, my team is already shipping solutions and moving faster than ever. Here's the truth: → Great leaders enable innovation. → AI tools amplify smart teams exponentially → Speed comes from empowerment, not oversight Stop managing innovation. Start enabling it. Here's the link to the tool: https://app.emergent.sh/ How are you empowering your team to experiment with AI in their workflows? Like & Repost to help your network embrace the future Follow Asim Khaliq for more insights on leadership, team empowerment, and scaling with AI. @

Human-centered technology strategy: start with the people! Technology isn’t inherently smart. It becomes smart when it helps humans thrive. Too many digital strategies forget the human in the equation, focusing instead on features, speed, and scale while overlooking the day-to-day reality of the people using it. If your tech plan doesn’t make work more meaningful, it’s just noise. If it doesn’t ease a burden or solve a real problem, it’s just expense. Start with talking to employees about what problems they need to solve or what challenges they need to address in their day-to-day. THEN, find a solution. Once you've implemented the solution, talk to employees again. 1️⃣ Ask how it improves their workflow. Does it reduce friction? Streamline what matters? Or does it create more steps, more checkboxes, more shadow work? 2️⃣ Ask what pain it removes. (Hopefully the one you uncovered in earlier conversations!) Every team has daily frustrations: manual tasks, duplicative systems, outdated interfaces. Tech should solve real pain points, not just chase the next big trend. 3️⃣ Ask how it adds meaning, not just speed. Efficiency matters, but so does purpose. The best tools create space for higher-value work: thinking, collaborating, listening, solving, building relationships. Human-centered technology isn’t soft. It’s strategic. Because adoption, productivity, and experience all rise when people actually want to use the tools they’re given. A “smart” strategy doesn’t just deploy tech. It designs for the people who power the business. For more details on putting people first, see the link in the first comment. #technology #digitaltransformation #culture #peoplefirst #employeeexperience #humancentereddesign #leadership

I often discuss strategy for public adoption of new technologies -- like autonomous aircraft and advanced air mobility -- as well as creative innovation strategies, whether for incremental, disruptive, and breakthrough innovation. These discussions are usually esoteric in nature, to encourage critical thought and mindset shifts. However, this time I'd like to offer something more concrete: a simple, practical strategy to address both adoption and innovation simultaneously. First, let's talk about first and second-order effects. When introducing something new, first-order effects are the immediate and direct results, while second-order effects are the indirect consequences that occur over time and are not immediately visible. These second-order effects, or "frictions," can significantly impact the success and sustainability of a technology (or project/product/policy, etc.). For example, New York City's rent control policy aimed to provide affordable housing for veterans but led to a decline in property quality and supply, creating unintended negative outcomes. Similarly, the introduction of smartphones increased productivity but also led to burnout due to the "always-on" culture. The silver-lining is that second-order frictions often reveal unexpected problems needing solutions, opening space for innovation, which I call the "third space." The third space is where innovative solutions emerge, creating new value and accelerating the adoption of first-order technologies. These "third space accelerators" make people more comfortable adopting the original technology. This approach as strategy involves: 1. Identifying likely second-order effects early. 2. Proactively developing third space solutions. 3. Presenting the complete ecosystem to drive adoption. 4. Using the existence of solutions to comfort potential adopters. Third space accelerators are strategic tools. By proactively developing third space solutions, we can better mitigate the negative impacts of second-order frictions and create innovative opportunities that drive adoption and innovation simultaneously. With the example of smart phones, third space solutions like digital wellness apps and wellness integration into workspaces emerged to address these new challenges, but only after the fact. I encourage you to apply this strategy in your projects: identify potential second-order effects early, develop solutions to address them, and present a comprehensive ecosystem that includes both the problem and the solution. This approach will not only facilitate smoother adoption but also foster continuous innovation. #innovation #leadership #technology #influence

Adoption killer: Asking users to change how they work. Instead of forcing new habits, why not wrap your tech around the ones they already have? That’s the genius behind Robin Cowie’s approach with Skillmaker.AI. It helps train auto techs up to 8x faster than traditional training by mbedding critical knowledge into the gear they already wear. It’s the opposite of a typical enterprise rollout: → No long onboarding → No behavior change → No new systems to learn One key example? Smart glasses. Familiar form factor = zero ramp-up Voice + AI = instant, hands-free answers at the point of work Old Way: Need torque specs? → Stop what you’re doing → Clean your hands → Walk to a terminal → Log in to the portal → Search for the vehicle → Find the spec → Walk back → Resume the job __________________________ New Way: Just ask: “F-150, 2020 model, engine block—what’s the torque spec for these bolts?” → Answer shows up in your glasses in under four seconds. → No context-switching. No friction. No slowdown. ________________________________ The key move: Design for your user’s routines, tools, and instincts The smart glasses work because they look like what techs already wear. Voice triggers work because hands stay busy. Information sticks because it’s delivered in-context, not classrooms. Key lesson for tech founders building tools for the field: Innovation isn’t just what you build. It’s how naturally it gets used. __________________________ For founders building in regulated, hands-on, or legacy sectors, our conversation shows how to build real-world products that win trust fast: We also cover: • How Blair Witch’s $60K constraint became its superpower • The risk that made Madden NFL unforgettable • Why “credibility” is the most underrated product spec • The real reason new tech gets adopted (or doesn’t) • What most founders get wrong about deployment Catch our full sit-down here: https://lnkd.in/eUpueM_w

𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝘄𝗮𝗻𝘁𝘀 𝘁𝗼 𝗯𝗲 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 🥇 𝘁𝗼 𝗯𝗲 𝘀𝗲𝗰𝗼𝗻𝗱 🥈 Sounds counter-intuitive when all the buzz is about leading from the front and racing ahead, right? 𝗪𝗲𝗹𝗹 𝗻𝗼𝘁 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗻𝗲𝗲𝗱𝘀 𝘁𝗼 𝗵𝗮𝘃𝗲 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗮𝘀𝗽𝗶𝗿𝗮𝘁𝗶𝗼𝗻. 📍For everyday procurement organisations, quality functions or finance teams being an early adopter of new technology may sound enticing but may not be an advantage if aiming to go beyond piloting. 𝗤𝘂𝗶𝘁𝗲 𝘁𝗵𝗲 𝗰𝗼𝗻𝘁𝗿𝗮𝗿𝘆! Being the first to adopt unproven tech may not pay off at all. It may incur unnecessary risks and costs. In some industries like Life Sciences, with regulated processes being first may result into an uphill battle with regulatory bodies and auditors who are building up their views on validation and compliance needs. 📍It's not always the "𝗲𝗮𝗿𝗹𝘆 𝗯𝗶𝗿𝗱 𝘄𝗵𝗶𝗰𝗵 𝗴𝗲𝘁𝘀 𝘁𝗵𝗲 𝘄𝗼𝗿𝗺" but often, its that one "𝘄𝗵𝗶𝗰𝗵 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗲𝗹𝘆 𝗴𝗲𝘁𝘀 𝘁𝗵𝗲 𝘀𝘁𝗼𝗿𝗺". A tactic in athletics is to let others lead the race, whilst you observe in second position, learn, adapt, and when appropriate, seize the moment to leap ahead. Being first to be second has its own merits for example with certain use cases in GenAI & other cutting edge technology: 1️⃣ 𝗥𝗶𝘀𝗸 𝗿𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻 by letting others pave the way and identify the pitfalls and challenges to apply new technology so that you don't bear the same risks 2️⃣ 𝗣𝗿𝗼𝘃𝗲𝗻 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻, building upon what others have already have done and leveraging their learnings to adapt and succeed. 3️⃣ 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 through the application of existing assets, processes and solutions others have already built saving costs and time. 4️⃣ 𝗟𝗼𝗻𝗴-𝘁𝗲𝗿𝗺 𝗳𝗼𝗰𝘂𝘀 by not jumping at the next trend or technology without considering how it fits into the overall strategy & plans. Not every trend fits with your business and technology roadmap. 5️⃣ 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 can be critical and may require the support of auditors and regulatory bodies. Whilst there is absolutely reasons for co-innovation with technology partners, these choices need to be inline with the risk appetite and resilience to accept failure. First to be second instead, means having the wisdom to watch, learn, and adapt and the intelligence to understand when the right moment to get involved to benefit from early adoption with caution. 📌It's about studying the pioneers, understanding their successes and failures, and leveraging that knowledge to refine your own strategy. ❓Have you ever found success by being "first to be second"? ❓When do you think being first is a better strategy Looking forward to your experiences and insights in the comments below! 👇 Reshare if you liked this post and hit the bell in my profile to follow me. #innovation #leadership #continuousimprovement #procurement #artificialintelligence

Adoption no longer hinges on the technical capabilities of AI systems. Yet, most tech leaders are still operating within an outdated framework as they push to deploy faster models in the hopes that it will drive sales. Instead, AI adoption is a reflection of three core beliefs: 1. Humans desire control 2. Technology is developing faster than people can adopt 3. Human failure is tolerated more than machine failure These three factors produce Societal Thresholds – invisible barriers to technological adoption. In application, these thresholds explain why AI in healthcare triggers completely different responses than AI in criminal justice, despite similar technical capabilities. Adoption uptake across domains entirely depends on whether innovations respect or hastily bypass these thresholds. Essentially, societal sentiment and readiness is the real challenge facing AI integration. My team and I have compiled our research into a white paper that challenges how we think about AI adoption. The full report is currently available on our Substack and will soon have a permanent home on my site.

The potential of AI is generating significant excitement, yet conversations with peers in the network across various functions and levels indicate that implementing AI is often complex. Beyond general productivity applications, effective AI deployment requires tailored solutions to meet specific use cases. The costs associated with team training or building custom solutions can be difficult to justify in the short term based solely on ROI. Several strategies are proving to be effective in maximizing the benefits of this rapidly evolving technology: Empowering through Dedicated Roles: Establishing specialized teams or roles within existing teams to manage AI-driven tasks can be impactful. Although this approach involves business process reengineering, which entails its own costs, it enables AI to integrate seamlessly into workflows. This allows employees to focus on their core strengths while AI is leveraged where it adds the most value. Focusing on High-Impact Areas: Prioritizing areas where AI can deliver significant value—such as by uncovering new insights or driving efficiency in previously manual tasks—helps ensure the technology is used strategically. Industry leaders are already adopting several general strategies to drive AI adoption: Investing in Accessible Tools: As AI tools advance, selecting solutions that are intuitive and accessible to all employees can transform AI from a specialized tool into a practical asset that empowers teams and opens new possibilities across the organization. Creating a Culture of Learning and Adaptation: Fostering an environment that supports continuous learning and adaptation is essential. When employees feel empowered to explore new technologies, AI adoption becomes a collaborative journey, driving growth, creativity, and resilience. As AI technology advances, with more customizable platforms and tools, adoption costs will likely decrease, making broader use cases viable and justifiable through ROI. These are indeed transformative times as we await disruptive innovations that will further extend the boundaries of what’s possible. #AI #ROI #Strategy

After helping dozens of companies adopt AI, I noticed something important: Every organization can benefit from AI—but the key is knowing which level of adoption makes sense. In practice, I’ve seen companies stuck between over-investing in complex solutions they’re not ready for—or under-investing in off-the-shelf tools that can’t scale. The reality? There are three practical tiers of AI adoption. Choosing the right one depends on your goals, process complexity, trust in AI, and expected ROI. ➡ Tier 1: SaaS Tools – Quick wins, but hidden long-term costs and limited flexibility. ➡ Tier 2: Low-Code Automations – Affordable and flexible; ideal for connecting existing tools and processes. ➡ Tier 3: Custom AI Solutions – Full control and long-term competitive advantage, but higher initial investment. The biggest insight? You don’t have to start big. Start where it makes sense, prove value, and build from there.

As our world gets more interconnected with smart cities, digital twins and XR, AI. sensors, we are facing new unprecedent risks. Connecting the future of business- a recent study by Kaspersky, reveals that over 50% of companies worldwide have already integrated AI and IoT technologies into their operations, with another 33% planning to do so within the next two years. This rapid adoption highlights not just the potential of these technologies to revolutionise business processes but also the cybersecurity challenges they bring. Why This Matters: ✏️Rapid Integration: Businesses globally are quickly incorporating AI and IoT, aiming to leverage their benefits for efficiency and innovation. ✏️Cybersecurity Risks: Approximately 16-17% of organizations find AI and IoT particularly challenging to secure, underscoring the need for robust cybersecurity measures. Kaspersky's Insights: Skills Gap: A notable gap in cybersecurity knowledge and skills is becoming a critical concern, as pointed out by Adrian Hia, Kaspersky's Managing Director for Asia Pacific. Recommended Strategies: ✏️Secure-by-Design: Emphasizing the importance of designing products that are inherently secure. ✏️Upskilling: Highlighting the need for continuous learning and development in cybersecurity. ✏️Advanced Solutions: Encouraging the adoption of cutting-edge security solutions to stay ahead of threats. The Bottom Line: The integration of AI and IoT is inevitable and beneficial but comes with its share of challenges. Companies must prioritize cybersecurity, embracing strategies that ensure robust protection against emerging threats. It's not just about adopting new technologies but securing them effectively to safeguard our digital future. Your Thoughts? #smartcities #technology #innovation #AI

𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 3: 𝐒𝐦𝐚𝐫𝐭 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐚𝐬 𝐭𝐡𝐞 𝐊𝐞𝐲𝐬𝐭𝐨𝐧𝐞 𝐨𝐟 𝐃𝐞𝐯𝐢𝐜𝐞-𝐭𝐨-𝐂𝐥𝐨𝐮𝐝 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲, 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞, 𝐚𝐧𝐝 𝐓𝐫𝐮𝐬𝐭 As IoT applications become increasingly integrated into critical aspects of business and daily life, the demand for enhanced security, compliance, and trust intensifies. This prediction highlights the growing need for smart connectivity solutions that address these concerns head-on. 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬: 📌𝐄𝐥𝐞𝐯𝐚𝐭𝐞𝐝 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬: The critical nature of IoT applications necessitates unparalleled data protection. Organizations must now guard against theft, alteration, and compliance violations more rigorously. 📌𝐒𝐦𝐚𝐫𝐭 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐟𝐨𝐫 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞: As IoT expands into areas like carbon trading, ensuring data security and compliance with regulations like GDPR becomes crucial. This requires secure, auditable routing within specific geographic limits. 📌𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐑𝐞𝐬𝐜𝐮𝐞: Advanced software libraries are emerging to provide essential smart connectivity. These tools will bolster device-to-cloud security and compliance, maintaining ecosystem trust. 📌𝐂𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐎𝐧-𝐃𝐞𝐯𝐢𝐜𝐞 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲: Essential security features, including authentication and encryption, must be embedded directly within devices. Technologies like TPM and IoT SAFE standards are pivotal in this regard. 📌𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬: These solutions serve as implicit agents for security management. They ensure secure, compliant routing through SDNs and blockchain, enhancing auditability. 𝐌𝐲 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐬: The evolution of IoT into critical business and life domains brings to light the indispensable role of smart connectivity in ensuring security, compliance, and trust. From an organizational perspective, the transition toward smart connectivity is not just a technological upgrade but a strategic necessity. Here's why: 📌𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐈𝐦𝐩𝐞𝐫𝐚𝐭𝐢𝐯𝐞: For organizations, adopting smart connectivity is essential to protect sensitive data and comply with stringent regulations. It's a strategic move towards building a secure, trustworthy digital infrastructure. 📌𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐚𝐧𝐝 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬: While integrating these sophisticated connectivity solutions offers a pathway to enhanced security and compliance, it also presents challenges. These include navigating complex regulatory landscapes and implementing robust security protocols. 📌𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧: Successfully deploying smart connectivity solutions requires collaboration between tech providers, regulatory bodies, and organizations. It also opens new avenues for innovation in security and compliance technologies.