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Tahawul Tech
2 days ago
- Business
- Tahawul Tech
Enterprise AI Execution Gap Archives
Mahmood Lockhat, Chief Technology Officer at TeKnowledge, discusses the execution gap faced by many organisations when it comes to AI and how their new partnership with aims to address this in this exclusive op-ed.
Tahawul Tech
2 days ago
- Business
- Tahawul Tech
Opinion: TeKnowledge CTO on the Enterprise AI Execution Gap
Mahmood Lockhat, Chief Technology Officer at TeKnowledge, discusses the execution gap faced by many organisations when it comes to AI and how their new partnership with aims to address this in this exclusive op-ed. Introduction: The AI Execution Challenge There's no question about it, Artificial Intelligence (AI) is transforming how businesses operate, improve customer interactions, and foster innovation. Yet, despite recognizing AI's vast potential, many organisations struggle to fully integrate and scale it within their daily operations. This 'execution gap' is exactly what the partnership between TeKnowledge and aims to bridge. In today's rapidly evolving digital landscape, enterprises face a fundamental conundrum: while AI technologies have reached unprecedented sophistication, the gap between AI ambition and real- world execution is still a reality that many enterprises are faced with. While we're surrounded by headlines about AI breakthroughs, many of us in enterprise technology are facing a frustrating reality in what I call 'The Pilot Paradox' running impressive demos that never translate into enterprise-wide transformation. We have brilliant AI pilots running in isolation, executive teams asking when we'll see real business impact, which needs to be delivered at scale. The partnership between and TeKnowledge isn't just another vendor, partner announcement it's a recognition that successful AI transformation requires more than just great technology. It needs a fundamentally different approach. Why Most AI Transformations Fail: The Missing Dimensions After years of watching AI implementations succeed and fail, I've learned that technology is just one piece of the puzzle. The organisations that truly succeed with AI get five critical dimensions right: Technology is the foundation, but it's not enough on its own. You need a platform that can evolve from simple chatbots to sophisticated multi-agent orchestrations. has cracked this code with their AI Agents Operating System, moving enterprises from guided intelligence through to full autonomy while maintaining human oversight. Data Readiness is where most projects stumble. Your AI is only as good as your data, and enterprise data is messy scattered across systems, trapped in silos, mixing structured databases with unstructured documents. TeKnowledge's expertise in data strategy and integration becomes crucial here, ensuring your AI agents have access to clean, relevant, and contextual information. Cybersecurity can't be an afterthought anymore. We're not just protecting data; we're securing AI models against adversarial attacks, preventing bias, and ensuring our AI agents don't become security vulnerabilities. TeKnowledge's cybersecurity practice understands these unique challenges and builds protection into every layer of the AI stack. Governance separates successful AI implementations from chaos. As we move toward super-agents managing multiple AI systems, we need frameworks that ensure accountability, transparency, and regulatory compliance. This isn't just about policies—it's about embedding governance into the platform architecture itself. Digital Skills might be the biggest gap of all. Your people need to understand how to work alongside AI agents, how to prompt them effectively, and how to maintain and evolve these systems over time. TeKnowledge's comprehensive skilling programs ensure your teams can grow with your AI capabilities. A Strategic Convergence: Platform Intelligence Meets Expert Services The partnership between a global market leader, expert in conversational, enterprise AI, and TeKnowledge, a leader in technology services including AI, customer experience, and cybersecurity, combines our strengths to help businesses scale AI smoothly and effectively. brings to this partnership a mature, agent-first platform that has evolved beyond the traditional chatbot paradigm. has pioneered the transition from guided intelligence to full autonomy through their AI Agents Operating System, spanning from reliable conversational bots to sophisticated autonomous agents capable of human-like interaction. offers a user-friendly yet powerful AI orchestration platform designed to boost productivity, efficiency, and customer service. Their technology easily understands what users want, communicates clearly with different systems, and performs tasks independently. This flexibility helps businesses integrate solutions into their existing systems, adapting quickly to changing technology. provides a comprehensive solution stack which is built around 3 major pillars: AI for Service – Enhances customer experience through intelligent virtual assistants, agent support, and contact centre optimisation. AI for Work – Increases employee productivity via workplace assistants (HR, IT, internal ops) and enterprise workflow automation. AI for Process – Automates end-to-end business processes with advanced AI-driven orchestration. Their platform addresses the three areas where businesses need AI most: reimagining work (helping employees be more productive), reimagining service (creating better customer experiences), and reimagining process (automating complex workflows). But here's what matters, they've built this with enterprise realities in mind. TeKnowledge complements by providing strategic guidance, advisory and precise execution to ensure AI projects deliver real business value. With over 6,000 experts across 19 global hubs, TeKnowledge makes sure AI implementations are strategic, measurable, and adaptable. We also stress and recognize the importance of being prepared with quality data, strong cybersecurity, effective governance, and digital skills, viewing these as essential for successful AI transformations beyond just technology. Creating Real, Lasting Impact What makes this partnership different is our shared focus on human-centric AI. Both TeKnowledge and believe AI should simplify interactions, improve business operations, and deliver clear, measurable benefits, such as improved efficiency, exceptional customer experiences, and innovative solutions. Gartner predicts that by 2028, 95% of businesses will integrate generative AI into their daily operations, a significant increase from just 15% in 2025. This rapid growth emphasises the need for businesses to strategically adopt AI. Gartner also notes the rapid advances in multimodal and agentic AI, promising to transform automation and improve user interactions significantly. The partnership helps organisations stay ahead of these trends. Similarly, Boston Consulting Group (BCG) emphasises the crucial role of CEOs and leadership in successfully implementing AI, warning that disconnected AI solutions—or 'AI islands'—can limit potential benefits. This partnership addresses these issues directly by providing an integrated, scalable, and well-governed AI ecosystem, enabling businesses to fully realise their AI investments. The Partnership Synergy: Providing End-to-End Solutions Here's why this partnership excites me as a CTO it addresses the complete AI transformation challenge, not just the technology piece. From Fragmentation to Integration: The partnership addresses the AI Chaos which many enterprises are facing today, the overwhelming array of hyperscalers, open source vendors, Agent AI, Intelligent Virtual Assistant solutions, CCaaS and enterprise ecosystems that create decision paralysis. By combining unified platform with TeKnowledge's structured implementation methodology, enterprises gain a clear path from concept to capability to business value Skills That Scale: TeKnowledge's skilling programs mean your people can actually use and evolve the AI capabilities. This isn't just about using AI, it's about building internal capabilities to innovate with AI continuously. Security by Design: With AI models becoming potential attack vectors, TeKnowledge's cybersecurity expertise ensures protection is built in from the start. We understand AI-specific threats like prompt injection, data breach and leakage, model poisoning, adversarial attacks, and bias exploitation. Data That Works: TeKnowledge helps organisations get their data ready for AI, not just accessible, but clean, contextual, and structured for use effectively within enterprise AI orchestration. Governance That Scales: As you move from single-purpose chatbots to orchestrated super-agents, governance becomes critical. The partnership provides frameworks that ensure accountability while enabling innovation. The Super-Agent Future: What's Coming Next In the coming year, we will witness the rise of what I call 'Super-agents' Powerful AI operating systems that coordinate multiple AI agents simultaneously. These advanced systems will significantly enhance organisational decision-making and problem-solving capabilities, guiding enterprises smoothly from basic intelligence to partial or full autonomy, always within human oversight. Imagine having a team of highly skilled professionals tirelessly working round the clock, resolving issues, streamlining processes, and executing transactions seamlessly, without downtime or interruptions. The growth in AI agent autonomy will revolutionise industries by optimising networks, enhancing fraud detection, streamlining patient care, personalising customer experiences, boosting employee productivity, and automating routine tasks. This shift allows employees to focus on more strategic, higher-value tasks, leading to faster decision-making, better performance, and accelerated business operations across all sectors, from product development, marketing to sales and customer support. We're also heading towards a future defined by AI-first customer experiences. AI will significantly improve customer interactions through complete, end-to-end orchestration, providing a personal assistant experience across sectors like banking, travel, healthcare, and retail, offering assistance, solving problems, and enabling seamless transactions around the clock, without us even noticing we're interacting with AI. offers the platform for this AI operating system future, enabling organisations to build, maintain, measure, and manage AI agents, systems, and orchestration. While provides the orchestration platform for these super-agents, TeKnowledge ensures organisations have the expertise and support to implement, govern, and evolve these sophisticated AI ecosystems responsibly with real business value. Why This Partnership Matters Now As we navigate the AI revolution, the question isn't whether to adopt AI, it's how to do it effectively at scale. The and TeKnowledge partnership provides a proven path that addresses the complete transformation challenge. For technology leaders, this partnership offers what we've all been looking for: a comprehensive approach that combines mature platform capabilities with the strategic services, security expertise, data readiness, governance frameworks, and skills development necessary for sustainable AI transformation. The reality is that successful AI transformation requires both technological sophistication and human expertise. It needs platform intelligence and strategic services. It needs innovation and governance. It needs automation and human insight. This partnership delivers all of that; not as separate services you have to coordinate, but as an integrated approach designed to help enterprises move from AI ambition to AI impact. And in a world where the pace of AI innovation continues to accelerate, having partners who can help you navigate both the technical and human dimensions of transformation isn't just valuable, it's essential. The future belongs to organisations that can harness AI's transformative potential while maintaining the human-centred approach that drives real business value. The and TeKnowledge partnership provides exactly that foundation for success. Image Credit: TeKnowledge
Tahawul Tech
08-04-2025
- Business
- Tahawul Tech
Opinion: ‘Bridging the AI Gap – From Hype to Enterprise Transformation' – Mahmood Lockhat, TeKnowledge
Mahmood Lockhat, Chief Technology Officer at TeKnowledge, outlines the best practices and measures that enterprises need to adopt in order to bridge the AI Gap, and turn the hype into tangible transformation in an exclusive op-ed for Bridging the AI Gap: From Hype to Enterprise Transformation: Over the past few months, I've had the privilege of engaging with industry leaders, analysts, and C-level executives from global organizations. One recurring theme has emerged: AI is at the centre of innovation, yet there's a significant gap between its potential and its current enterprise adoption. This article explores four critical themes shaping AI adoption today: The gap between AI expectations and reality Steps for integrating AI into organizations Measuring success in AI initiatives Emerging trends that will shape the future of AI The Reality Behind AI's Hype Cycle Let's start by putting the current landscape into context. Over the past few decades, we've witnessed transformative platform shifts in computing: the Internet gave us universal access to knowledge, smartphones placed that knowledge in our hands 24/7, and cloud computing made digital resources globally accessible, revolutionizing business operations. Now, AI is giving us tools to unleash intelligent productivity in unprecedented ways. According to McKinsey, generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually to the global economy across various use cases. What makes AI unique is its status as a general-purpose technology, accessible to all, regardless of age, location, or profession. From farmers in India increasing crop yields in challenging agricultural areas to specialized oncologists in the US and UK being able to identify cancer early, allowing focused treatment plans; AI's reach is extensive. Gartner predicts that by 2026, enterprises that implemented AI will see a 25% improvement in customer satisfaction, employee productivity, and operational efficiency compared to those that don't. In our personal lives, AI has become an on-demand assistant providing information, advice, and recommendations. Five years ago, having instant access to expertise in law, medicine, education, travel, and cooking would have seemed impossible. Yet, here we are, leveraging AI assistants. However, this creates a challenge: while we expect enterprise AI to be as seamless as consumer AI, the reality is highly nuanced, due to security, governance, ethics, data sovereignty, uptime, and ROI considerations. Enterprise AI must focus on targeted use cases that deliver measurable business outcomes. Four Key Factors Creating the Expectation Gap: Unrealistic Expectations: The 'hype cycle' of impressive demos and bold predictions naturally elevates expectations. BCG reports that 70% of digital transformations fall short of their objectives, often due to inflated expectations and underestimated complexity. Despite remarkable progress, AI isn't magic. People expect fully autonomous solutions without appreciating the necessary data, infrastructure, and expertise requirements. Data Quality & Implementation Challenges: AI effectiveness depends on good data, yet many organizations struggle with fragmented, messy data. According to PwC, 86% of executives report their organizations struggle with data quality issues when implementing AI. Integrating AI into existing systems is rarely plug-and-play. Lack of Clear Business Objectives: Companies often implement AI without defining the problem they're aiming to solve or how they'll measure success. AI must integrate into the overall business strategy with monitored, measured outcomes. Skilling and Adoption: Perhaps, most critical is the people component. Technology deployment alone isn't enough: employees need appropriate training to use AI effectively. Digital skilling ensures your workforce can maximize the impact of AI tools like Microsoft Copilot. IDC predicts that the shortage of skilled AI professionals will be cited as the number one barrier to AI adoption in 60% of organizations. Takeaway: To close this gap, enterprises must focus on targeted use cases that deliver measurable business outcomes while addressing challenges like data quality, governance, and workforce readiness. Designing an Effective AI Integration Plan Having led major AI-driven transformations across industries like telecoms, aviation, financial services, and government, I've seen firsthand what works—and what doesn't—when integrating AI into organizations. I've learned that a strategic approach is essential: Start with Clear Goals: Identify specific business problems where AI can add value. Where are processes slow or inefficient? Where can customer experiences be improved? Target real issues, not technology for its own sake. PwC's 2025 AI Business Predictions report emphasizes that nearly half (49%) of technology leaders have already fully integrated AI into their companies' core business strategies. This is echoed by Accenture, who report that companies with a clear AI strategy tied to business objectives, achieve 3-4x the ROI compared to those without. Assess Your Data Foundation: AI needs quality data. Evaluate your data's quantity, accuracy, and accessibility. Data organization and cleanliness are crucial preliminary steps. A study by MIT and Databricks found that companies that excel at data management see 3x better results from their AI investments. Begin with Pilot Projects: Avoid attempting comprehensive transformation at once. Start with small, focused pilots that demonstrate clear results to build confidence and organizational learning. Focus on People: Invest in the right talent, including emerging roles like Chief AI Officer, Prompt Engineer, Data Scientist, and AI Architect. Equally important is ensuring attention to data privacy, security, compliance, and ethical considerations. BCG's research underscores this point, noting that 'companies need to focus two-thirds of their effort and resources on people-related capabilities' when undertaking AI transformations. Success comes when: Clear objectives make AI purposeful High-quality data makes AI reliable Successful Training makes AI an integral part of the organisation Measuring AI Success How do you know if your AI initiatives are successful? The answer lies in building a clear scorecard and ROI model before starting any project. Key metrics to consider include: Efficiency and Productivity Gains. As a 'Customer Zero' organization actively using AI tools like Microsoft Copilot, we measure daily time savings per employee. With comprehensive training and adoption, we're seeing approximately 30-45 minutes saved per employee per day. This aligns with Microsoft's own research, which found Copilot users completed tasks 29% faster and were 37% more productive. Other efficiency metrics include : reduced processing times, increased output, lower error rates. Customer Experience Improvements. Track improvements in CX through, measuring metrics such as: Customer Satisfaction (CSAT) and Net Promoter Scores (NPS), Increased wallet share per customer, First Contact Resolution (FCR) rates, Interactions completed with zero human touch through Automation, Reduced Average Handling Time, and decreased employee attrition. Accenture's research shows that companies implementing AI-powered customer experience solutions see up to a 15% increase in customer satisfaction and a 40% reduction in service costs. Financial Impact. Being able to measure the ROI is essential. In order to see the value that the investment in AI is yielding, tracking financial KPI's such as the ones below is required: R educed operating costs, educed operating costs, increased revenue, sales, profitability human time/costs saved through automation These are all fundamental to your ROI calculation. BCG found that companies that successfully implemented AI saw a 10-15% increase in revenue and a 10-20% reduction in costs across operations where AI was deployed. Takeaway: By tracking these metrics against baseline measurements, organizations can clearly demonstrate the value that AI brings to their operations. According to Accenture, 74% of organizations have seen investments in generative AI and automation meet or exceed expectations, with 63% planning to increase their efforts by 2026. The Next 12 Months, AI within Digital Industries. While predicting more than 12 months ahead is challenging, I'm most excited about AI projects moving from pilot phases to enterprise-scale production environments, driven by autonomous agents and agentic AI. The industry needs to progress beyond one-off technology showcases to deliver tangible business outcomes – improved efficiency, lower costs, and better service. Autonomous agents and agentic AI will enable this shift. Imagine having 10 new team members who; are highly qualified, work independently to resolve issues, streamline processes, and complete transactions – without requiring sleep, sick days, or time off. McKinsey estimates that about 30% of hours currently worked in the US economy could be automated by 2030, and agentic AI will accelerate this trend globally. We'll likely see the emergence of 'superagents' – AI systems orchestrating multiple specialized AI agents, enabling more complex problem-solving and independent decision-making. This trend will transform every industry – optimizing networks, improving fraud detection, streamlining patient care, and enhancing both customer and employee experiences. Most importantly, it will free human employees to focus on more complex, valuable tasks. The Future of Customer Experience The future is AI-First Customer Experience – using AI to improve customer lives through end-to-end experience orchestration that provides a personalised, human-like personal concierge available 24/7 across any channel – so seamless that customers won't know they're interacting with a machine. According to PwC, 75% of business leaders believe that AI will deliver better customer experiences in the near future. Conclusion: Unlocking AI's True Potential AI is no longer a futuristic concept—it's here now, reshaping industries and redefining how we work and live. However, realizing its full potential requires more than just deploying technology; it demands clear goals, robust data strategies, skilled people, and measurable outcomes. PwC's analysis is clear: 'Businesses that fail to integrate artificial intelligence into their operations will fall behind'. Companies must move beyond viewing AI as experimental technology and instead position it as a core business driver. At TeKnowledge, we're committed to helping organizations bridge the gap between hype, and reality, through advisory services, digital skilling programs, and innovative CX and AI solutions. Through our strategic partnerships with Microsoft, Genesys, and other technology providers, we can help our customers with their AI strategy and transformation journey.
