McKinsey UK and Ireland’s Post

💡 Working with DTC Brands across industries, AI Is Top of everyone's Mind! 💡 I’m frequently asked about AI implementation in their respective functions. According to the latest estimates from McKinsey, 65% of companies worldwide have implemented AI models—either in the pilot or production stages. 🌍🤖 But with a plethora of AI tools and platforms out there, businesses can feel overwhelmed. How do you choose the right solution for your functional and infrastructure use cases? 📝 This McKinsey report offers a great framework for CDOs and Chief AI Officers to scale GenAI successfully. Here are my key takeaways: 1️⃣ Operating Model: Develop a model that aligns people, processes, and technology to deliver the most value. In addition, build continuous Measure, Test, & Learn cycles. 2️⃣ Component-Based GenAI: Focus on critical components in the early phases—think APIs for data inputs, vector databases, Agents, Hallucination Checkers, and more. 3️⃣ Team Org Structure: Whether you choose a centralized or decentralized AI strategy depends on your organization’s structure and communication practices. 4️⃣ Risk & Compliance Management: Establish a baseline risk assessment and compliance framework, revising it as new risks are identified. check out the full report from McKinsey here: https://lnkd.in/gbnBYefR #AI #GenAI #DataScience #DigitalTransformation #McKinsey #Innovation #Leadership

🔍 Measuring the business impact of AI use cases    Generative AI has been seen everywhere in 2024, and now businesses are getting used to utilizing these tools daily. While the technology's value is evident, leaders now face the challenge of measuring and tracking that value.  The importance of tracking impact  🔊 "Most organizations struggle to measure their impact due to a lack of performance management infrastructure... they lack a clear methodology to quantify and monitor their effectiveness. Organizations must develop this capability." – Matthew Fitzpatrick, a McKinsey Senior Partner and Global Leader of QuantumBlack Labs.   This article from QuantumBlack, AI by McKinsey by Matthew Fitzpatrick, with additional insights from Mohammed ElNabawy, and Rohit Rathod, examines challenges faced by organizations when measuring #AI impact, such as aligning stakeholders, defining metrics, isolating financial impact, and ensuring #data accuracy.   Success can be found by distinguishing between model performance and business performance. Additionally, top performers have been found to prioritize business impact tracking, following a four-step approach to ensure effectiveness:  🔹 Define and align on leading and lagging KPIs  🔹 Ensure the feasibility of chosen indicators  🔹 Automate and integrate into a portfolio to track value rigorously  🔹 Communicate the impact    👉 Discover how measuring the impact of AI use cases can benefit your business and leadership in today's AI-driven operations: https://lnkd.in/euhSdj_i

CIO Influence BCG Henderson Institute Organizations That Create New KPIs with AI Are Three Times As Likely to See Greater Financial Benefit #AI #AIenriched #analytics #digitaltransformations #FinancialBenefit #KPIs #leveragingAI #Organizations https://lnkd.in/dTeq6hEg

A McKinsey survey found that only 10% of organizations implement regular/systematic tracking of the value their AI/genAI initiatives. I spoke with DataIQ about how while most companies are experimenting with trying to scale AI (with mixed results), the real challenge for most business leaders is how to define and track the value of these initiatives. Model performance tracking is a staple of the ML lifecycle, and most companies get it right. But top performers know how to focus on business impact tracking (e.g., revenue uplift) as well, which is harder but also what really matters in terms of ROI. The most effective organizations take a four-step approach: 1) Define and align on leading and lagging KPIs 2) Ensure the feasibility of tracking chosen indicators 3) Automate and integrate into a portfolio to track value rigorously 4) Communicate the impact effectively to stakeholders and the broader organization

AI is transforming the business landscape - but how are companies capturing the ROI? A new study from MIT is revealing valuable insights on how AI can reshape industries - and it's a powerful lesson for businesses that are struggling to define clear ROI metrics on their AI investments. In a controlled trial, over 1,000 scientists using AI tools for materials discovery saw an incredible 44% increase in discovery rates and a 39% jump in patent filings. However, these gains were far from universal. The benefits of AI were primarily driven by scientists who already possessed high levels of domain knowledge and judgment skills. What are the takeaways for businesses looking to implement AI? 1.       AI is only as effective as the expertise behind it. While AI accelerates data analysis and decision-making, its success depends on the skills of those using it. In the study, top-performing scientists used their experience to interpret and prioritise AI-generated insights - a capability less-experienced colleagues struggled to match. 2.      The importance of ‘judgment augmentation’. AI is fantastic at automating routine tasks, but it doesn’t get rid of the need for human expertise (yet); it shifts it. The study found that AI decreased time spent on idea generation by 57% while increasing judgment-based tasks by 74%. So, a profession that once prized creativity now finds itself increasingly filled with “evaluative” roles. This offers a clear message: AI doesn’t currently eliminate the need for judgement and decision-making. This shift in the core nature of work should be a central component of ROI assessments. 3.      The Threat to Job Satisfaction and Talent Retention. Among these scientists, the shift toward evaluation over creativity led to a predictable drop in morale, with 82% reporting lower job satisfaction. For business, this should be a warning: AI that relegates intelligent, creative individuals to the role of an umpire over AI suggestions risks reducing employee satisfaction - and by extension, the quality of their work. The big question is: how should businesses measure the ROI of AI? Most companies continue to measure success by speed and efficiency, rather than by the level of innovation and the quality and impact of the insights AI enables. This study makes it clear that AI doesn’t eliminate human input; it reshapes it. Successful companies will be those that measure AI ROI by the value it brings to human judgment, adaptability, and innovation - not just efficiency. The hard truth is this: many businesses are still struggling to make sense of AI’s role within their organisations. Perhaps it’s time for a more discerning view of AI - one that recognises it as a tool for the wise and an amplifier for the talented. Anything less might risk not only diminishing returns, but diminishing people themselves. https://lnkd.in/ek4qzfTM #AI #DigitalTransformation #technology #Innovation #BusinessStrategy

Is your business prepared for the future? AI is no longer a futuristic concept. It is a transformative force reshaping industries and redefining how businesses operate. But the question remains: Is your business ready to embrace the future with AI? 𝐖𝐡𝐲 𝐀𝐈 𝐑𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 AI has the potential to revolutionize your business, offering numerous benefits such as increased efficiency, improved customer experiences, and data-driven decision-making. However, to leverage these advantages, your organization needs to be AI-ready. This means having the right infrastructure, skills, and strategy in place to integrate AI effectively. 𝐒𝐭𝐞𝐩𝐬 𝐭𝐨 𝐄𝐧𝐬𝐮𝐫𝐞 𝐘𝐨𝐮𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐬 𝐀𝐈-𝐑𝐞𝐚𝐝𝐲 - Assess Your Current Capabilities: Start by evaluating your current technological infrastructure. Do you have the necessary hardware and software to support AI initiatives? Assess your data quality and storage capabilities, as AI relies heavily on large volumes of high-quality data. - Build a Skilled Team: Having a team of skilled professionals is crucial for successful AI implementation. Encourage continuous learning to keep your team updated with the latest AI trends and technologies. - Develop a Clear AI Strategy: Define your AI objectives and align them with your business goals. Identify areas where AI can add the most value, whether it's improving customer service, optimizing operations, or enhancing product offerings. Having a clear strategy will guide your AI initiatives and ensure focused efforts. - Ensure Data Readiness: AI systems thrive on data. Ensure that your data is clean, well-organized, and accessible. Implement robust data management practices to maintain data quality and integrity. Consider using advanced analytics to gain insights from your data before applying AI solutions. - Start Small and Scale Up: Begin with pilot projects to test AI applications in a controlled environment. This allows you to learn, adjust, and measure results without significant risk. Once successful, gradually scale up your AI initiatives across the organization. - Collaborate with AI Experts: Partnering with AI experts can accelerate your AI journey. Companies like Cybrix 360 AI specialize in helping businesses integrate AI solutions. They can provide the expertise and tools needed to implement AI effectively and efficiently. - Monitor and Adapt: AI is a rapidly evolving field. Regularly monitor your AI systems' performance and stay informed about new advancements. Be ready to adapt your strategy as needed to keep pace with technological changes and emerging opportunities. Preparing your business for AI is not just about adopting new technologies; it's about fostering a culture of innovation and continuous improvement. At Cybrix 360 AI, we are committed to helping businesses navigate the AI landscape. Contact us today to explore how we can enhance your business with AI and ensure you are ready for the future.

Great insights fom Mckinsey on the state of AI Adoption for the first half of this year. Its clear that early movers are seeing big bottom line benefits and are also carving a pathway for others to follow - if they can keep up! These early movers are also calling out the challenges that they are hitting up against with seventy percent saying they have experienced difficulties with data, including defining processes for data governance and in developing the ability to quickly integrate data into AI models. Solving for data management and governance is a difficult challenge, especially if we continue to look at this problem with the pre-AI era data approach. Capturing mountains of data and trying to sort it for use. The AI era has different demands and so our approach to data management needs to also shift. Gone I would argue is the era of trying to sort mountains of data. To a simpler era of asking for the data you need and ensuring you get this data. A new challenge but when addressed correctly provides the data that AI needs to be activated quickly and safely. https://lnkd.in/eEY463HA

While artificial intelligence's potential to transform industries is undeniable, its successful implementation hinges on clearly defined business objectives and responsible deployment strategies. According to an EXL survey, for AI to have a meaningful impact, firms must prioritize data optimisation. Click for more details & insights: https://lnkd.in/dDpr5M82 #leadershipchallenges #futureofbusiness #business #datascience #AI #machinelearning #businessintelligence #businessstrategy #digitaltransformation #leadership #growth #success #teamdevelopment #gpt4 #remoteteams #innovation #collaboration #techtalent #futureofwork #futureskills #teamepic

Using #AI and #Analytics to discover undervalued and influential #KPIs will improve decision making and drive positive outcomes. One important factor for broader adoption of these concepts in organizations is the need for strong data literacy foundation (i.e., explore, understand and communicate insights) within organizations. #GenerationD

The Intelligent Business and Seven Habits of the Highly Effective Data Enabled, AI Powered Business: Since coining the 7 Habits of the Highly Effective CDO 2 years ago so much has changed that I have further refined the model to the 7 Habits of the Highly Effective Data Enabled, AI Powered Business aka The Intelligent Business. In essence: Data is both the fuel of the business, and the material from […] The post The Intelligent Business and Seven Habits of the Highly Effective Data Enabled, AI Powered Business appeared first on The Digital Transformation People.