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#GenerativeAI has the ability to disrupt how businesses operate—but its success will depend on a clear understanding of the business challenge and operational readiness. Explore our collection of insights to understand the application and adoption of generative AI across the operations value chain and unlock strategies for capturing its value in operations. It should be deployed as a part of digital transformation, not merely seen as a technological advance. Learn more ➡️ https://mck.co/3wYoF1i #Technology #Operations

Here are some reasons why new technologies like Generative AI might fail to yield business value: 1. *Lack of clear use cases*: Without a deep understanding of how the technology can address specific business needs, adoption may be slow or unsuccessful. 2. *Insufficient integration*: Failing to integrate new technologies with existing systems and processes can limit their impact. 3. *Inadequate training and support*: Without proper training and support, users may struggle to effectively leverage new technologies. 4. *Unrealistic expectations*: Overhyping the capabilities of new technologies can lead to disappointment and disillusionment. 5. *Failure to measure ROI*: Not tracking the return on investment (ROI) of new technologies can make it difficult to justify their adoption. To ensure new technologies like generative AI yield business value, it's crucial to: 1. *Identify clear use cases* and align them with business objectives. 2. *Develop a comprehensive integration plan*. 3. *Provide robust training and support*. 4. *Set realistic expectations* and communicate them effectively. 5. *Establish metrics to measure ROI* and monitor progress. By taking a thoughtful and strategic approach to adopting new technologies, organizations can maximize their potential and drive meaningful business value. Maayu AI Prabakaran Murugaiah T. Scott Clendaniel Ruben Hassid Rubén D. Linas Beliūnas

This graph highlights key touchpoints for leveraging gen AI throughout the customer journey. A valuable addition could be incorporating gen AI to analyze and categorize customer feedback and complaints in the final stage of the journey. Gen AI addresses the challenge of capturing and analyzing raw data by providing insights from customer inputs. By enhancing customer support processes, organizations can meet demanding SLAs more effectively. Automation of issue resolution and continuous improvement through the Deming cycle further enriches the customer journey. #AI #CustomerExperience #DataAnalysis #Automation #CustomerSupport

Trust in AI is needed to realize the benefits of this transformational technology. Digital trust has the potential to enable AI to be a force for good, offering organizations the opportunity to prioritize the management of digital risk and accelerate their operations through the amplification of technology, so they are ideally positioned to thrive. Here are three #digitaltrust considerations to get you started: Digital society strategy: What does the digital society mean to you? Digital by design: What role does digital play in your organization? Consumer trust: Where does consumer trust feature on your #transformation agenda? Addressing these questions now has the potential to set organizations up to harness the power of technology for the future – see some examples of how AI is starting to have a positive impact on different industries and organizations here: https://bit.ly/4bggZFS

While private equity firms typically seek proven, profitable technologies, some firms are starting to invest in AI and even leverage the technology in their own dealmaking. In an article with Middle Market Growth Magazine, Baker Tilly’s Travis M. Drouin shares insights on how the use of AI at a company may impact future waves of PE investments. Read more: https://bit.ly/3xeaOnJ  #AI #PrivateEquity #Technology 

I've seen my share of tech trends come and go. But the buzz around Generative AI is different. It's not just the ability to churn out catchy marketing copy or write basic code – it's the potential to fundamentally transform how we work. McKinsey's latest article reinforces this sentiment. While I appreciate their insights on talent management and risk mitigation (essential aspects, no doubt!), what resonates most with me is the call to operationalize generative AI. Here's what I'm focused on: Building vs. Buying:  We need to stop celebrating flashy demos and start building robust, scalable solutions that solve real business problems. The "Taker-Shaper-Maker" framework is helpful, but I'd argue most organizations will need to embrace a hybrid approach to leverage both readily available tools and customize models with proprietary data. This requires striking a delicate balance between speed, cost, and competitive differentiation. The Skills Evolution: While upskilling existing teams is crucial, I believe the report understates the seismic shift about to hit the data science talent landscape. Generative AI demands a new breed of expert. Yes, we'll need those who can fine-tune models and wrangle complex datasets. But even more critical will be those with the deep analytical capabilities to critically evaluate model output, identify biases, and make informed decisions about when to trust (or override) a machine's recommendations. We need to treat this looming talent gap with the same urgency as building the technology itself. The Data Imperative: Those who've already tackled data architecture modernization are going to have a head start. The report rightly stresses that access to quality, contextualized data is everything for these models to perform as promised. Collaboration is Key: This isn’t just a tech play. Success hinges on fostering strong collaboration between business and technology teams to identify valuable use cases, align on priorities, and ensure responsible deployment. Generative AI is integrated at all key touchpoints to enable a tailored customer journey. While next-gen tech like generative AI can cause a flurry of excitement, it can also lead to business bottlenecks. We must navigate these challenges with a strategic approach. Generative AI is not a magic bullet, it's a powerful tool that requires a strategic and practical approach to deliver transformative impact. Let's move beyond the hype and start building the future. #GenerativeAI #DigitalTransformation #AIstrategy #DataStrategy #Innovation #DataScience #AI

There is no doubt that AI provides an opportunity for competitive advantage if implemented well, but both the strategy and internal adoption can provide challenges for businesses. Check out some strategies for getting your team on board: https://lnkd.in/gbqWmyW4. #aiadoption #aistrategy

AI is revolutionizing business today, driving efficiency, productivity, and faster decision-making. Start small, focus on measurable gains, and prioritize data quality and change management. Embrace innovation while providing structured guidance to stay competitive. Learn more about AI's impact here:

In the midst of ongoing debates, we believe in the power of collaboration. 100% automation with AI may not be on the horizon, but the real intrigue lies in AI's potential as a creative partner, enhancing experts' capabilities. The journey and discussions continue, and as we look ahead to 2035, the possibilities are endless. Let's get ready for the future together. 🛡️💡 #AI #Innovation #MarTech #LinkedIn

Neudesic’s Tech Vision provides a vision for executives to navigate the technology landscape and their roadmaps, focusing on transformative technologies that reshape business strategies. The 2024 vision spotlights AI with actionable guidance to inspire and navigate tomorrow. Download today: https://lnkd.in/gfKbWrWz #artificialintelligence #responsibleai #genai #aiops