nutrād’s Post

With two simple words: Augmented + Connected - Gartner makes clear the real difference between next-gen AI systems and the frustrating database/spreadsheet-driven core of today's Supply Chains... For decades, Supply Chain Professionals have invested tremendous time and serious capital to organize their product data. So why aren't global chains more productive and less costly? When Supply Chain workers add content to a database or spreadsheet they are organizing their data in the same way one would organize documents in a file cabinet. Christian Titze, Dwight Klappich, and the Gartner Supply Chain practice suggests a 2024 trend, the "Augmented Connected Workforce" will become the "connective tissue that optimizes the use of intelligent technology, workforce analytics and skills augmentation." Rather than simply dump critical trade and product data into a digital file cabinet, Supply Chain Professionals can now use AI-based tools to Augment (improve) data and Connect (share) data in ways impossible with database, data pool, or spreadsheet-driven solutions. This is transformational thinking and will lead to significantly more functional and less costly global chains.

Gartner states that data labeling and annotation have reached the plateau of productivity, indicating they are now mature and are mainstream capabilities. In one way, Maturity can be judged by how fast objectives evolve vs how quickly organizations adapt. Fast evolving objectives - With data-centric AI and LLMs, the need for this capability has intensified I would argue and more required than ever. Slow adoption in enterprise - While the market might be showing maturity, the life sciences and healthcare sectors lag surely. Siloed efforts to clean data are common, org wide domain-specific initiatives are rare usually Many data product owner initiatives in enterpises are still in early to mid-stages best case. The capabilities arent as mainstream yet atleast - Given the need for expert judgment and the consequences of data labeling in the Lifesciences domain . These are many times manual and extremely expensive to be done at scale. Approaches which seamlessly combine Tech with Human expertise are rare The plateau of productivity in Life sciences seems distant in my view atleast. Do you see it differently

Worldwide revenues for the AI market are projected to reach $327.5 billion in 2024, with a YoY increase of 20.6%. This is a testament to the continued strong investment in AI despite economic downturns. AI software is expected to account for over half of all AI spending in 2024, followed by AI services and AI hardware. Big data and analytics software will make up more than 40% of all AI software spending. According to IDC, the three industries that will spend over $15 billion each on AI systems in 2024 are banking, retail, and healthcare providers. Retail leads industries with expected AI spending of $19.8 billion. The US and China will continue to dominate AI spending globally, with the US spending $124 billion and China spending $70.6 billion. However, China is expected to experience faster growth rates over the next several years. Strong growth is expected in worldwide AI spending across software, services, and hardware, with retail, banking, and healthcare industries leading the way. Source: IDC

"GenAI and automation will enable organizations to drive $1 trillion in productivity gains worldwide by 2026." New figures from the IDC really put gen AI's impact into perspective. This year Gen AI will evolve from being a tool for efficiency to a driver of top-line growth: https://lnkd.in/egbtNJCY.

Last year Gartner launched a #survey for collection insights about the expected benefits form the huge #ArtificialIntelligence investments. The results from the 608 CIOs and technology leaders participants are under your eyes: 1️⃣ Improve #productivity / #efficiency (77%): The bulk of respondents (77%) expected AI to drive improvements in productivity and efficiency (to automate tasks, minimize manual labor, and optimize processes within organizations for example); 2️⃣ #Cost Reductions (50%): Half of the respondents anticipated that AI will assist in reducing operational costs (potentially to optimize resource usage, minimize human error, but also about the staff, rearrangements or different optimization); 3️⃣ #Enhance customer experience (56%): Over half (56%) anticipated that AI will enhance the customer experienc (individualized, prompt, and effective interactions, such as chatbots, recommendation systems, or customized services); 4️⃣ Increase #agility and #responsiveness (53%): AI is also supposed to make companies more flexible (53%). For example to make faster and better decisions, adjust to changes in the market, and meet customer needs right away; 5️⃣ Drive digital #transformation (53%): Artificial Intelligence (AI) is widely recognized as a crucial facilitator of digital transformation. As tool that empowers to transition from conventional processes to more sophisticated, data-driven methodologies, thereby promoting innovation and ensuring their long-term viability; 6️⃣ Drive #innovation (50%): AI is expected to contribute directly to driving innovation, with 50% of respondents seeing it as an essential factor in creating new products, services, and business models. Almost 1 year later... do you feel the same? 🤔 💡 I am running a new poll in the Gartner Peer Experiences you can join in too: https://lnkd.in/d37msKGi where some additional options have been added: 7️⃣ Promote Internal #ChangeManagement 8️⃣ #Other (for those who have already different vision). #Innovation #Disruptive #Technology #Business #Strategy #Adoption

One week left to register for our exclusive webinar, "Being Data-Ready to Fully Embrace Gen AI." Join industry leaders Giovanni Cervellati (IDC) and Abhiram Mahajani (Factspan) as they explore: ➔ The current state of Gen AI adoption in businesses ➔ Strategies for leveraging Enterprise Data effectively ➔ Secure and efficient solutions for integrating Gen AI Don't miss out! Secure your spot today: Register Now 🔗👉 https://bit.ly/3vtwThs #GenAI | #Webinar | #Data | #IDC | #Factspan | #Livesession

Half of supply chain leaders are planning to implement generative AI (GenAI) in the next 12 months with another 14% claiming they have already begun implementing the technology within their organization, according to a Gartner survey. According to a report published by Gartner's Supply Chain Practice January 10, only about 2% of respondents said that they have no plans to implement GenAI in their operations over the next 12 months. The study also showed that companies are backing up their implementation plans with financial support. Supply chain leaders have said that they will allocate 5.8% of their budgets on average to this technology. Additionally, 65% of responders said they will hire staffers and experts to deploy GenAI technology within their organization. “CSCOs see GenAI as supportive of their broader digital transformation objectives,” said Noha Tohamy, a VP analyst in Gartner’s Supply Chain Practice. “Many supply chain leaders were already leveraging supply chain technologies and advanced analytics, and it’s clear from this data that the majority also see the value in GenAI to enhance productivity, improve business agility and reduce costs. The challenge for many of these organizations over the next 12 months will be in scaling their pilot projects to broader adoption… CSCOs may also be factoring in impacts on employee roles required of their staff as they shift to higher value-add activities, while lower-level tasks are increasingly automated.” #GenAI #ArtificialIntelligence #FutureOfWork #TechnologyTrends #Innovation #DigitalTransformation #DataScience

🚀 In a recent Gartner survey, 70% of CIOs see Generative AI (GenAI) as a game-changing technology, signaling a significant shift in the digital landscape. Additionally, 64% of CIOs are adopting or planning to deploy low-code platforms within the next 24 months, reflecting a growing trend toward democratizing digital delivery. 💡 As an AI company at the forefront of innovation, we're excited about the transformative potential of GenAI and the simplicity of low-code solutions in driving seamless business automation. If you want to learn more about how Reshape AI can help your business leverage our low-code platform and take full advantage of AI within your processes book a fully tailored demo: 📅 https://lnkd.in/g2FAPyyv or contact us here: ✉ https://lnkd.in/eSczfAdS

🚀 Unlock AI potential in your supply chain with Gartner’s 7 data quality focus areas. Read the full report for actionable insights! https://bit.ly/3L1cm7R #SupplyChainAI #DataQuality

Gartner's latest report, "Over 100 Data, Analytics, and AI Predictions Through 2030," highlights the profound impact of data, analytics, and AI on industries worldwide. The predictions underscore the accelerated pace of AI adoption, the crucial role of data management, and the ongoing transformation of business landscapes. For leaders in data and analytics, these insights are essential for shaping strategic initiatives and driving future innovation. Five Key Takeaways: AI and Data are Driving Business Transformation: By 2027, data and AI will be critical to business strategies across sectors, with over 60% of CDAOs needing to deliver data literacy and AI culture changes to stay relevant. Generative AI is Reshaping Industries: By 2028, 70% of AI-generated SaaS applications will become composites for enhanced digital engineering, emphasizing the rapid evolution of AI technology in business applications. Governance and Ethical AI: By 2027, 60% of organizations will fail to realize the value of their AI use cases due to weak governance frameworks, highlighting the need for cohesive ethical AI governance. AI’s Role in Decision Intelligence: By 2025, 60% of analytics and business intelligence platforms will integrate decision intelligence capabilities, revolutionizing how businesses make data-driven decisions. The Rise of GenAI in Business Operations: By 2028, GenAI will be embedded in 80% of workplace applications, driving substantial improvements in productivity and operational efficiency. These predictions provide a roadmap for leaders to harness AI and data to drive competitive advantage and operational excellence. Note : Link to full report available at comments section