Balancing Technology With Work

Adopting AI tools is easy. Reimagining how we work with them is the real transformation. Across many organizations, teams are being asked to “adopt AI” without the time, training or clarity they need to feel confident. When that happens, progress becomes fragmented—some people race ahead, others hesitate, and morale drops under the weight of confusion. Real AI transformation requires more than deploying technology. It demands deeper shifts that help people work differently and unlock value: → Change management to guide teams through new ways of working → Skilling to empower every employee to thrive in an AI-powered environment → Process understanding to ensure AI augments what matters most → Technology that’s usable, ethical and aligned with business goals As this Forbes article shares, the organizations that succeed will be the ones that treat AI adoption as a human journey, not just a technical one. When teams feel equipped, supported and included in shaping the path forward, that’s when AI truly delivers. What support are you giving your teams to learn and experiment with AI? https://lnkd.in/g2pXBtjm

Technology isn’t a cost center, it’s your competitive edge. If you can’t shift this perspective, you won’t be able to innovate ���� Over the past decade, I've guided numerous companies, from pharmaceutical giants to financial leaders, on their journey to becoming product-led. One common mistake I've seen is treating technology as a mere expense, not a strategic advantage. This view undermines transformation efforts. Here's how it unfolds and what to do about it. In many organizations, technology is seen as a cost center. When executives talk strategy, it's often about cost reduction. They can articulate market differentiators well but stumble when asked, "How does your tech vision enhance your competitiveness?" Silence. The competitive edge dulls as rivals leveraging tech strategically catch up. This approach is like playing corporate whack-a-mole: solving cost issues while missing opportunities. What if the process you streamlined wasn't needed at all? Or if you could innovate beyond traditional methods? Many transformations start with Agile to address slow development cycles. But speed alone doesn't equate to success. Agile without product thinking can lead to an output-focused mindset: success measured by backlog clearance rather than solving real business problems. Transformations stall when teams build features quickly without building the right ones. It's crucial to view software products as strategic enablers, not just tools to "run the business." Without this shift, product strategies remain uninspiring. Even if your software isn't sold, it can be a major strategic differentiator. Consider Capital One's journey: disrupting the banking sector by using data analytics for credit risk models and improving customer experiences by eliminating unnecessary processes. What about internal tools? For pharmaceutical companies, bringing drugs to market is essential. Instead of merely speeding up processes, your tech could identify study participants and predict outcomes better than competitors. It's about asking the right questions. "How do I make this cheaper?" leads to outdated solutions. "How do we re-imagine this process for an exceptional experience?" drives innovation. If you're on this journey, start by changing the conversation. Ask "why?" and "what if?" Shift from cost-cutting to value-creation, from outputs to outcomes, from project management to product thinking. Real transformation isn't about new processes or team reorgs. Those are secondary. The core shift is viewing technology as a strategic asset driving business value. That’s where the real transformation begins.

Transformation thrives when people are empowered to make the most of technology. 🚀 My recent visit to the Bosch production facility for automotive and eBike drives in Miskolc, Hungary, showcased this perfectly. I was deeply impressed to see firsthand how their progress in digitalization and the implementation of the Bosch Manufacturing and Logistics Platform (BMLP) is reshaping their manufacturing operations. BMLP is a globally standardized, open IT platform that connects all stages of production and logistics. During an insightful plant tour, I observed a successful example of how the platform leads to significant improvements in efficiency, quality, and data transparency across the plant. What stood out most was seeing the passionate and enthusiastic team at Miskolc leverage this technology in action and achieving great results towards operational excellence. Here are three key areas where BMLP is contributing to the plant’s digital transformation success, powered by our NEXEED IAS: 1️⃣ Enhanced Efficiency & Reduced Downtime: The module Shopfloor Management enables a closed PDCA cycle in production by consequent integration of all relevant information in one system. This leads to quick reaction in case of deviations to minimize downtimes and safeguard the daily performance targets.   2️⃣ Improved Product Quality: Continuous monitoring throughout production stages helps the team identify issues early, ensuring top-tier quality while driving process improvements.   3️⃣ Change Management: Change management plays a crucial role in digital transformation within a plant. As seen in Miskolc, effectively managing change ensures that the workforce is engaged, and equipped to embrace new technologies, driving sustainable success. In Miskolc we have seen solutions using gamification that help to involve all associates, making the transition both engaging and effective.   I was also excited to see AI in action with a live demo of 8D Analysis using GenAI, cutting failure analysis time by half. By automating the root cause analysis process, engineers are now spending less time on administrative tasks and more on proactive problem-solving – a great example of how technology empowers people. Beyond the production lines, the most rewarding part of the visit was engaging with the team. Their passion for digitalization, commitment to upskilling, and their drive for innovation truly brought home the message: technology is only as strong as the people behind it. A special thank you to the entire Miskolc team for the inspiring discussions and warm welcome – along with Volker Schilling, Klaus Maeder, Joerg Klingler, Volker Schiek, Norbert Jung, Stephan Brand, Aemen Bouafif, and everyone who joined us on this great trip. I’m excited to see what’s next on this incredible digitalization journey!

For businesses adopting AI, the promise of savings through role automation can mean the human cost is overlooked.    I’ve noticed plenty of optimism about AI freeing humans from repetitive jobs, but a deeper concern is also emerging: if businesses continue to rely on traditional career paths and capability frameworks, human workers may find themselves sidelined in the future of work.   Whilst the perceived benefits of AI freeing up human time for more strategic roles is attractive, the consequent rising unemployment and lack of training for young professionals is alarming. How can our people effectively make these strategic decisions in the future, if they miss out on the fundamental learning and development offered by entry-level roles?   For long-term commercial success, it is clear businesses have a responsibility to take care of their people and support employees to adapt to the future of work with AI.    🌱Grow your people by investing in reskilling programmes so your team is properly equipped with competitive capabilities to harness AI. 👥 Foster an ethos of human-AI collaboration by amplifying and nurturing the qualities that make us unique – creativity, intuition, compassion and imagination to optimise the benefits of AI augmentation rather than AI replacement. 🤝 Build trust by committing to mitigating any detrimental effects of the technology on people and society and providing transparency and safeguarding around the development and deployment of AI.    Now is the time for business leaders to consider how you are helping workers adapt in the new AI world. And for workers, is your business doing enough?

This manufacturing CEO wanted to replace his 20+ person team with AI. Here’s why I - an AI founder - advised against it: 2 weeks ago, I met a warehouse owner who struggled with packing and storing foreign-sourced products. Their team received products with labels in Chinese and Vietnamese, but they lacked a proper solution to identify items correctly. Products were stored in the wrong boxes, misplaced, and shipped to the wrong customers. To help, I suggested using a vision-based AI assistant to - Scan the packaging text - Analyze the language & meaning - Instruct the worker where to store it The owner thought this was a good idea and immediately began thinking about the money he could save and the staff he could replace. This line of thinking is a huge mistake. Viewing AI as a cost-cutting and workforce replacement tool creates short-term savings at the expense of long-term growth and productivity. He shouldn't think of using AI to fulfill these tasks alone. Instead, I recommended he think of how AI can make their workers' life easier and better. In his situation, workers can spend less time doing repetitive tasks (sorting through items) and more on delivering quality service to their customers and achieving more with ease and less stress. This approach is more meaningful and engaging, improving both staff output and company culture. So: Cutting costs and replacing employees with AI isn't the highest leverage way to use it in your business. Instead, think of how you can use it in tandem with your staff so that it augments their productivity and output to a level you've never thought possible. Make their life easier and aim for greater productivity and output. Don't replace them with machines 🙂 P.S. If you're curious on profitable AI use-cases for your business, send me a message or email me (ck@incepteo.com) and I'll work with you to brainstorm some options, free of charge.

I automated my entire team's workflow—and then THIS happened. Ever wonder what would happen if your team could complete a week's worth of work in a single day? Sounds like a dream, right? Well, that's exactly what we achieved. A few months back, I noticed my team was bogged down with repetitive tasks. Brilliant minds were spending hours on mundane activities. So, I decided to take a bold step. We invested in automating these tasks. The initial push was challenging: - Learning new tools - Changing long-standing processes - Overcoming resistance to change But the payoff was incredible. Results: - Productivity skyrocketed: We accomplished more in less time. - Stress levels dropped: The team felt less overwhelmed. - Innovation flourished: Free time led to creative solutions. - Employee satisfaction increased: Work became more fulfilling. The most surprising outcome? Our team cohesion strengthened. With less time on grunt work, we collaborated more on strategic projects. The takeaway? Automation isn't about replacing people. It's about freeing them to do what they do best. Embrace technology to unlock your team's true potential. Have you implemented automation in your work?

How GCC Leaders Can Improve Work Execution to Drive Employee Experience, Productivity, and Quality Most GCCs focus on scaling operations and cost efficiencies, but the best leaders go beyond that. They rethink how work gets done—removing inefficiencies, empowering employees, and ensuring quality outcomes. Here’s what truly moves the needle: 1. Fix Process Inefficiencies and Automate the Obvious Too many GCCs still replicate HQ processes instead of optimizing for agility. Identify bottlenecks, eliminate redundant approvals, and automate manual tasks—especially in IT, HR, and finance. Workflow automation can cut task times in half. 2. Align Teams Across Time Zones with Outcome-Based Execution Global teams struggle with coordination, leading to handover gaps and rework. Instead of micromanaging, real-time dashboards, and clear outcome ownership. Focus on customer impacting outcomes not effort. 3. Empower Employees with the Right Tools and Autonomy A poor employee experience leads to low engagement and productivity loss. Give teams self-service analytics, knowledge bases, and low-code/no-code tools to solve problems independently. Cut meeting overload and encourage deep work time. 4. Prioritize Learning, Growth, and Cross-Functional Expertise GCCs shouldn’t just execute work—they should drive innovation. Invest in technical upskilling, global mobility programs, and leadership rotations to create a future-ready workforce. 5. Governance Without Bureaucracy Traditional governance models slow down execution. Instead of rigid top-down approvals, implement agile decision-making frameworks and RACI models that balance control with speed. GCC leaders must shift from process execution to work transformation—optimizing workflows, leveraging AI, and making employee experience a top priority. The results can be significant: • 15-30% productivity gains by automating and streamlining workflows. • 10-25% cost savings through elimination of reduntang processes, process efficiencies and automation. • 20-40% improvement in employee engagement by reducing friction in daily work. • 20-50% faster execution of key projects by reducing delays and dependencies. • 25-50% fewer errors through improved governance and automation.

Have you noticed how AI agents just changed the conversation, moving rapidly from “interesting pilots” to agents quietly running parts of the work? This happens inside factories, service centers, finance teams, and supply chains. What feels different now is the tangibility and we should all follow this closely Bernard Marr’s latest post on LinkedIn show, how manufacturing captured this momentum well: Here, agents are no longer demos, they’re delivering real work. One example I like is a manufacturing copilot that turns decades of product documentation into an on‑demand expert for engineers and frontline teams. The result is faster onboarding, fewer blind alleys, and a measurable productivity lift. This is not wishful thinking, it's day‑to‑day decisions made better at scale, moving from pilots to real impact. I see strong movement in other areas as well. In customer service, multi‑expert assistants have replaced the former rule‑based bots. They understand intent, communicate effectively, pull live context, can do real business transactions and hand off to a human when needed. The value isn’t just efficiency, it is a significant step-up in experience for customers. Procurement is becomming lighter too. A supplier communications agent chases confirmations, interprets vendor emails, and proposes clean PO updates for a human approval. Teams spend less time on manual follow‑ups and more time on supplier strategy. Human in the loop, impact on the bottom line and happier employees. I could go on. The change I am experiencing is that we move from “AI adoption” to delegation. Which repetitive, rules‑bound tasks should an agent own in your business, and where do you still need human judgment in the process? Getting that balance right can unlock speed yet keep you in full control. So-  where to start? I will share a few simple inputs: 👉 Pick one process where ‘cycle’ time, error rate, or employee load is a known pain or significant task. 👉 Ground the agent in your data and policies - and access/decide the scope to work with. 👉 Measure three outcomes: Time saved, quality of output, and rework avoided 👉 Keep a human approval step where decisions carry financial, safety, brand or other tangible risks There is strong support to be found amongst our Danish IT and advisory companies to get started if this resonates. Don’t wait for the perfect plan but start with a single process,  learn and build on that. Let’s continue moving on the opportunities within the AI field and find credible proof of impact.

🚫 Don’t Automate the old mess…because you will just get a faster mess. I have witnessed , in far too many digital transformations, teams rushing to implement automation, AI, or workflow tools — driven by the excitement and hype of technology and the promise of efficiency. But more and more there’s an uncomfortable truth surfacing: 👉 If the roles and decision points are not clear, automation will make confusion move faster. 👉 If the underlying process is broken, automating it only multiplies the inefficiency. 👉 If the data is inconsistent, automation will replicate bad data at lightning speed. Automation amplifies whatever exists — good or bad. True digital impact doesn’t start with coding bots or deploying AI models. It starts with rethinking and redesigning processes around outcomes, not legacy constraints. That means taking an intentional and hard look at: • What steps actually add value to the customer or the business? • What can be eliminated, simplified, or standardized? • Where can we bring in technology to elevate, not just accelerate? When you invest time in process redesign first, automation becomes a force multiplier instead of a cosmetic fix. Transformation is not about digitizing legacy pain points. It’s about re-imagining how work should flow, and then using technology to scale that new logic. 💬 So next time someone says, “Let’s automate this process,” try asking: “Should this process even exist?” Because automation isn’t transformation.It’s optimization after transformation. #DigitalTransformation #ProcessExcellence #Automation #AI #Leadership #ChangeManagement #FutureOfWork