BCG's AI Value Gap study: How to succeed with AI

“Data is the new oil”… and I say AI is the new engine. 🚀 At the IBM Agentic AI Summit, two insights stood out: Hande Akdede Erbay explained what it means to be an AI-first enterprise. Not just adopting tools, but putting AI at the core of business strategy to unlock data’s full value and turn it into innovation, productivity, and growth. Melih Murat from IDC made it crystal clear: the era of AI experimentation is over. Winning enterprises will scale agentic AI with clear strategy, governance, and measurable results 💡 My takeaway: Technology isn’t a support function anymore — it’s the growth driver. And the Middle East isn’t just following the AI wave; it’s steering it. P.S. Having an AI wingman like Arsalaan Syed makes even the wildest agentic conference feel like a Marvel movie plot. 🎬🤖 👉 Follow me for more insights on enterprise AI, digital transformation, and leadership from Middle East and beyond. #AgenticAI #IDC #TechWithGokul #FriendlyNeighborHoodGokul

Great webinar on #ResponsibleAI by Dr. Venkata Dakshinamurthy Kolluru this morning. The conversation was deep, honest, and filled with practical insight about where #ArtificialIntelligence is headed and what it will take to make it trustworthy. 1. THE FIRST ACT OF RESPONSIBILITY IS USING THE RIGHT AI FOR THE RIGHT TASK There are many forms of AI. Generative models have captured attention, but they are not always the best solution. They are often more costly and less efficient for structured or repeatable problems that traditional machine learning can handle better. A responsible organization chooses its tools carefully and validates its architectures through independent review to ensure that performance, efficiency, and purpose align. 2. FOCUS & SIMPLICITY CAN OUTPERFORM SIZE Smaller, domain-focused models can achieve comparable accuracy to large models while using far less energy, cost, and data. They can also be trained to understand the unique context of an organization. In many cases, precision & control matter more than scale. 3. AI SUCCESS DEPENDS ON MORE THAN THE MODEL Data quality, workflow design, integration, monitoring, and governance determine whether an AI system endures.  As AI becomes easier to build, the surrounding infrastructure must become stronger. 4. RESPONSIBILITY INCLUDES SECURITY, BIAS, AND POSITIONING Enterprises are learning that AI must be designed with security in mind. Systems that can take or execute instructions must be governed to prevent unintended actions. Bias remains a central challenge because AI learns from human data, which reflects both progress & prejudice. Finally, AI should be positioned as an aid to human capability, not as a replacement. Some organizations that replaced entire teams with automation later reinstated people after realizing the limits of the technology. 5. RESPONSIBLE AI MUST BE LED FROM THE TOP Leadership must see AI not only as a technical program but as an enterprise capability. Dashboards that track explainability, fairness, sustainability, and reliability alongside accuracy can help align goals with outcomes. A small internal ethics group that includes business, legal, HR, and technical voices can ensure that responsibility is reviewed before deployment. The next phase of AI progress will not be defined by scale, speed, or creativity. It will be defined by credibility. The organizations that will lead in the next decade are those that treat responsibility as an engineering design parameter rather than as a public statement. https://lnkd.in/eVdBVTkn Soothsayer Analytics #AI #GenerativeAI #GenAI #DataScience #Leadership #Innovation #DigitalTransformation

Soothsayer has started a series of webinars on use of AI technology. Even if you already know a lot about how to use AI (or maybe, especially if you do), if this first installment is any indication, this is going to be a must-see series. This first installment on #ResponsibleAI was great. No hand-wringing or bandstanding, just a clear presentation of a lot of things that anyone who uses AI on a regular basis already knows, but put into a context of utility and ethics that provides a framework for how to think about these things (and how to change your behavior, based on that thinking).

📉 95% of generative AI pilots are failing. That’s the headline from MIT’s GenAI Divide: State of AI in Business 2025 report. Despite billions invested, most enterprise AI initiatives stall before delivering measurable impact. The issue isn’t the tech—it’s the organizational learning gap. Executives often blame regulation or model performance. But MIT researchers found the real culprit: poor integration, misaligned budgets, and a lack of workflow adaptation. Over half of AI budgets go to sales and marketing, while the biggest ROI lies in back-office automation. So before launching your next AI pilot, ask: Is your organization truly ready for AI? 🔍 Kanerika’s AI Assessment Tool helps you answer that. Evaluate your AI maturity across strategy, data, infrastructure, and talent—and get a custom report with actionable insights. 🧭 Try it here: https://buff.ly/jHUMMU9 #AIReadiness #GenAIDivide #Kanerika #DigitalTransformation #EnterpriseAI #AIAssessment #CFOInsights Bhupendra Chopra Amit Kumar Jena Samidha Garud Gaurav Verma Sushree Swagatika Varun Saket Valiveti Dylan Lurvey Zay Watson Ruba Diab Manisha Chowdari Nalla Sri Harsha Kadimisetti

The Stabilization Curve: What KPIs Will Define the Post-Upheaval AI Era? - https://lnkd.in/g4RfV8HV 🌟 Is AI Chaos Over? Experts Reveal Signs! 🌟 Our latest Techronicler article taps business leaders, thought leaders, and tech pros to pinpoint when the tech workforce and markets have fully adapted to AI. Here’s the scoop: - Stable Roles: AI augments, not replaces, with hybrid jobs thriving. - Predictable ROI: AI delivers reliable productivity gains, no trial-and-error. - Invisible Infrastructure: AI becomes routine, like plumbing in operations. - Strategic Shift: Teams focus on problem-solving, not repetitive tasks. - Trusted Decisions: AI predictions drive investments, like appraisals or reports. From standardized governance to casual client trust, these indicators signal AI’s upheaval is history. The Stabilization Curve: What KPIs Will Define the Post-Upheaval AI Era? - https://lnkd.in/g4RfV8HV Featuring insights from: Georgi T. Thomas Faulkner Manoj Kumar Casey Ryan Matthew Mccourry Erik Daley Chris Mignone Ryan Hall Damien Baden Visit www.Techronicler.com for tech insights that inform, innovate, and inspire! #Techronicler #Tech #AIMaturity #TechStrategy #AIROI #AI #Upskilling #DigitalTransformation #CTO

Boston Consulting Group (BCG)’s new report shows the AI value gap is widening fast. Only 5% of more than 1,250 companies are achieving value at scale, while 60% see little to no impact despite heavy spend. Another 35% are scaling but not yet delivering consistent results. The pattern is evident that many leaders treat AI as an enterprise capability, not a set of pilots. They tie AI to P&L outcomes, build strong data foundations, and industrialise delivery with robust governance. One standout insight is the rise of agentic AI. BCG estimates agents already account for ~17% of total AI value in 2025 and could reach 29% by 2028. The most mature future-built organisations are leaning in –dedicating meaningful budget to agents and redesigning workflows so humans and agents co-create outcomes. For everyone else, the takeaway is practical: prioritise a few high-value journeys, stand up shared platforms and guardrails, and measure business results, not model metrics, every quarter.  #agenticAI #digitaltransformation #AI #talent

🧠 𝐀𝐈 𝐀𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐈𝐬 𝐄𝐚𝐬𝐲, 𝐀𝐈 𝐌𝐚𝐭𝐮𝐫𝐢𝐭𝐲 𝐈𝐬 𝐍𝐨𝐭 Over 90% of organizations say they’ve deployed AI, yet few can truly show measurable impact. The gap? A lack of alignment between people, process, and technology. Many contact centers are still battling siloed systems, inconsistent data, and agent burnout, even with new AI tools in place. The truth is, success in AI isn’t about how many solutions you deploy. It’s about how aligned your organization really is. Before scaling your AI investments, start with a maturity assessment. Understand where you stand today, where the gaps lie, and how to maximize ROI. Because the companies winning with AI aren’t just deploying tools, they’re transforming how they work. 📊 Ready to see where you stand and explore what true AI readiness looks like? Learn more about our AI Readiness program here 👉 https://bit.ly/42yZhMl #AIReadiness #CustomerExperience #ContactCenter #AIMaturity Darren Prine Fred Stacey Jessica Voss

📈 The future of AI isn’t just predictive—it’s agentic. BCG X and Boston Consulting Group (BCG)’s latest findings show that agentic AI already drives ~17% of AI value today and is on track to nearly double to 29% by 2028. That means the companies building with agents at their core are set to capture the lion’s share of value creation. The winners? “AI-first” companies—those that: 1️⃣ Allocate larger shares of their AI budgets to agents (15% today). 2️⃣ Partner across ecosystems of infrastructure, platforms, and apps. 3️⃣ Redesign workflows to blend autonomous agents with human oversight. Meanwhile, laggards risk falling further behind, as unmanaged security risks and outdated processes block adoption. The message is clear: AI-first organizations are not only moving faster—they’re widening the gap. By 2028, the divide between future-built firms and everyone else could be unbridgeable. 🔑 Question for you: Do you see agentic AI as a short-term efficiency boost—or a long-term competitive moat? #AI #AgenticAI #BusinessTransformation #AgenticProcessAutomation #UpQuAI

🚀 Agentic AI isn’t just a trend—it’s quickly becoming the engine of real value creation. BCG’s latest findings confirm what we’re seeing every day: companies that invest in agents now are shaping the competitive landscape of tomorrow. Those that wait? They may find the gap impossible to close. For me, the most striking takeaway is how fast the shift is happening. Agentic AI is already driving close to 1/5 of AI’s value—and will almost double by 2028. The winners won’t be the ones experimenting on the side, but the ones embedding agents into the very core of their workflows. 👉 Curious to hear your perspective: will agentic AI be a short-term boost—or the long-term moat? #AI #AgenticAI #BusinessTransformation #UpQuAI

We do see tangible value in complex agentic workflows with real business impact - not just simple workflow orchestration, which is what the majority of so-called "AI agents" actually are.