Sean Patrick O'Brien’s Post

AI Adoption in the Enterprise: Get on Board or Get Left Behind? According to surveys from McKinsey, IBM, Forbes, Sortlist a staggering 77% of companies are either using or exploring the use of AI. However, the same data indicates there is still a sizeable portion of companies that have no concrete AI implementation plans yet. From personal experience, in the healthcare industry, there are three main reasons for this hesitation: 😨 General unease about disrupting current processes 💰 Budgetary constraints for investment 🛑 Unaware of AI's capabilities But what is the cost for businesses to stay on the AI sidelines? As transformative technologies like AI rapidly progress, taking a "wait and see" approach brings risks to: ✅ Falling behind more proactive competitors ✅ Missing valuable efficiency and productivity gains ✅ Struggling to leverage new opportunities. Companies and people choosing to deprioritize or ignore AI implementation may soon find themselves at a major disadvantage. Which path are you and your company currently traveling? Sources: https://lnkd.in/dY62wvQ9 https://lnkd.in/dTXRKp-a https://lnkd.in/dHBWYXVA https://lnkd.in/dDGarwKE

Recent research reveals that merely 30% of Taiwanese enterprises have embraced AI. Regardless of whether your organization is in the exploratory phase or actively implementing AI, it's essential to evaluate your internal capabilities—ranging from your infrastructure and data platforms to your technology—prior to formulating strategic plans. By investing in and enhancing five critical indicators, you can solidify your business's stance in the AI landscape and create a future-ready intelligent enterprise. Access the complete report (in Traditional Chinese) here: 👉 https://reurl.cc/93aeWX This report delivers a comprehensive analysis of enterprise AI strategies and practices, spotlighting opportunities for improvement across five key dimensions. It tackles essential challenges, including the need for adaptable governance in response to evolving AI regulations and the necessity to bridge skill gaps in AI model development and maintenance. Decision-makers will discover actionable insights within this guide, empowering them to harness AI through strategic planning, technical skill enhancement, and compliance-oriented security—effectively positioning themselves to excel in this transformative era. After reviewing this report, we encourage you to reach out to us, regardless of where your business is in its AI journey, so we can help you develop a powerful and competitive AI transformation strategy! #CloudMile #GoogleCloud #AI #GenAI

The insights provided by Nikhil Deshpande highlight that AI is not a replacement for the human workforce but a powerful tool to augment human capabilities and address workforce shortages strategically. By automating routine tasks, optimizing resource management, and enhancing decision-making, AI can help government sectors become more efficient and responsive. This, in turn, allows them to do more with less and ensures that they can continue to serve the public effectively despite workforce constraints. Learn more about how government agencies that strategically implement AI solutions while considering ethical implications and transparency can create a more agile, resilient, and future-ready workforce that is better equipped to handle the demands of modern governance on https://zurl.co/nqOZ #AIWithCAIO

Here are the essential lessons from practical AI implementations highlighted in the #TCS #AI study. Embracing responsible AI use and maintaining content integrity are fundamental as we navigate these innovations. Dive into the full report here. (https://lnkd.in/eUAaPGxd) 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗳𝗼𝗿 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗔𝗜 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: • 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴: Effective scheduling and preparation are crucial for successful AI deployment. • 𝗜𝗻𝘃𝗲𝘀𝘁 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Emphasizing robust data systems and ensuring high-quality inputs, including insightful human feedback, is essential. • 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗖𝗵𝗮𝗻𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Comprehensive change management strategies and continual adaptation are necessary for implementing AI successfully. • 𝗦𝗲𝗮𝗺𝗹𝗲𝘀𝘀 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: AI integration requires adaptability, effective communication, and continuous training across departments. • 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝗗𝗮𝘁𝗮 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Using secure platforms is critical to protect data integrity and ensure privacy. • 𝗘𝗻𝗰𝗼𝘂𝗿𝗮𝗴𝗲 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Address AI hesitancy among employees and provide necessary training and support. • 𝗗𝗲𝘃𝗲𝗹𝗼𝗽 𝗜𝗺𝗽𝗮𝗰𝘁𝗳𝘂𝗹 𝗠𝗲𝘁𝗿𝗶𝗰𝘀: Establish metrics to effectively measure AI's impact and assist in strategic decision-making. 𝗣𝗿𝗶𝗺𝗮𝗿𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗶𝗻 𝗔𝗜 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: • 𝗘𝗻𝗵𝗮𝗻𝗰𝗶𝗻𝗴 𝗜𝗧 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Modernizing existing IT systems to support advanced AI functionalities is crucial. • 𝗠𝗲𝗲𝘁𝗶𝗻𝗴 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗘𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀: Ensuring that AI-driven solutions align with evolving customer needs is essential. • 𝗡𝗮𝘃𝗶𝗴𝗮𝘁𝗶𝗻𝗴 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀: Addressing challenges presented by current IT service frameworks to maximize AI potential. #AI #EthicalAI #BusinessTransformation #TCS

Google has just updated its Generative AI Prohibited Use Policy, enabling customers to deploy generative AI tools in “high-risk” areas like healthcare. This is a significant shift that allows for the automation of decisions within these critical domains—but with one crucial caveat: human oversight must remain integral to the process. Here's what this means for companies venturing into automated decision-making: 1. Human Oversight Required: Even as organizations utilize Google’s advanced AI capabilities, ensuring a competent human review signifies accountability and ethical governance, especially where stakes are high. 2. Capabilities Expanded: With this clarification, expect enhanced efficiency and the potential for innovation as industries can leverage powerful AI solutions while still aligning with regulatory frameworks. 3. Risk Management: Businesses adopting these tools should actively engage stakeholders in risk assessment strategies—discussions on how supervision will work in practice are essential for successful implementation. 4. Stay Informed & Prepared: Companies must stay informed about ongoing policy changes and adapt their workflows accordingly to integrate compliant AI solutions effectively. This is an exciting yet cautious advancement in the role of generative AI across various sectors! How do you see this change impacting your industry? Share your thoughts or experiences below! #ArtificialIntelligence #GenerativeAI #HealthcareInnovation 🌐💡 Check out 🔔 gigabai.com 🔔 to automate your workflow today.

This month's State of Enterprise Tech Spending report from Battery Ventures, reinforces the need for #boards and CXOs need to be prepared to become #AI literate and fluent in order to monitor strategic impact and oversight responsibilities associated with #AI initiatives. A notable 60% of enterprises plan to increase their AI/ML spending in 2025, driven by its potential to enhance efficiency, automate processes and deepen data insights. This underscores the growing emphasis on AI/ML capabilities. This continued enthusiasm to harness the capabilties of #AI will drive acceleration and innovation across Enterprise, and #boards should be ready to support. https://lnkd.in/ec8KXN9X #AI #innovation #strategy #valuecreation

⚙️ How can IT service providers capitalise on the rising demand for AI? ⚙️ With many organisations lacking the in-house expertise for AI implementation, incumbent IT service providers can seize the opportunity by transitioning into ‘AI integrators’. Given that AI adoption is still in its early stages, these providers may achieve a first-mover advantage. CIL’s Technology practice explores how IT service providers can bridge the gap between AI’s potential and implementation. Read more in our latest insight piece here. #Technology #ArtificialIntelligence #AI #ITServices #CILInsights

How to scale your AI Solutions? Find a playbook on how to industrialize AI here: https://lnkd.in/ddJWReVc Next to adoption challenges, the book addresses the MAIVA framwork: MAIVA – AI strategy and platform planning MAIVA – Innovation, Intake, Experimentation MAIVA – the AI platform, the data platform, and the data (perpetual data strategy) MAIVA – Develop, Deploy & Operationalize AI/ML Use Case It is #opensource on #github

Salesforce has presented its UK AI Readiness Index, indicating that the UK is well-positioned to lead the next phase of AI innovation, particularly in agentic AI. The report highlights the UK's leading position in AI adoption among G7 countries but also notes areas that need improvement, such as support for small and medium enterprises (SMEs), cross-sector partnerships, and talent development. Zahra Bahrololoumi CBE, CEO of Salesforce UKI, said that agentic AI is transforming enterprise software by facilitating collaboration between humans and agents. Salesforce is investing $4 billion in the UK's AI ecosystem over the next five years, focusing on bridging regulatory approaches and enhancing digital skills. Read more: https://lnkd.in/dpM9Tvtg #ai #artificialintelligence