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From vision to value: A strategic approach to generative AI adoption

Generative AI has the potential to redefine productivity, create novel applications, and reinvent customer experience. But without a strategic approach, you could not only miss out on the promise of this powerful tool, but also drain time, energy, and resources away from other mission-critical initiatives across your organization. To that end, Kristen Backeberg, Director of Global ISV Partner Marketing at AWS, and Val Henderson, President and CRO at Caylent, recently sat down to discuss maybe the most important consideration around adoption: How to tailor your generative AI strategy around clear goals that can drive your organization forward. Their conversation started, like so many around generative AI, with an overview of especially high-impact use cases. However, both AWS and Caylent have helped dozens of organizations adopt generative AI, and Backeberg and Henderson understand that starting this journey can be daunting. The solution, according to both Henderson and Backeberg, is knowing which use cases are going to bring the most ROI. “[The first implementation] has to generate real ROI,” Henderson said. “Based on what we’re seeing, if it doesn’t, generative AI adoption loses steam and attention. It loses momentum. That’s not good for anybody, because we’re seeing such incredible innovation, and the speed of that innovation has never been faster.” In addition, focusing on customer experience provides a clear North Star for AI initiatives. By focusing less on buzzwords and more on clearly defining the system’s purpose, organizations can drive effective development and performance. “People are always going to want to understand the why,” Henderson added. “Why did we do this? Did we do it to check a box, or did we do it because it helps us move our vision, our desire to help our customers, to create a better experience moving forward?” By building together on top of Amazon Bedrock, Caylent has been able to help 50+ customers across even the most stringently regulated sectors adopt generative AI solutions, proving that this approach is a powerful way for organizations to bring use cases to life. “This is where AWS feels good about trying to make sure that we’re continuing to think differently,” Backeberg said, “think bigger, think outside of the box, and bring together the pieces along the way that create some of the necessary guardrails while we develop this space.” Listen to the full conversation to learn more about how to maximize the ROI of your generative AI initiatives with a clear, strategic framework on AWS.    source

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Salesforce adds Testing Center to Agentforce for AI agents

Sandboxes, according to Salesforce, work by mirroring images of an enterprise’s production data and configurations. “By replicating the enterprise’s data and metadata into a risk-free environment, development teams can rapidly assemble their unstructured data foundation and rigorously prototype Agentforce without fear of disrupting the business,” the company explained in a statement.   From testing to production Once enterprise users determine that the agents are functioning as required, they would be able to deploy the changes using proprietary tools such as Change Sets, DevOps Center, and the Salesforce command line interface (CLI), the company said. source

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CIOs view cost management as possible AI value killer

Cost is certainly a concern when CIOs think about deploying gen AI, says Yuval Perlov, CTO at K2view, a data management vendor. In its own recent survey of senior AI deployment professionals, K2view found that cost was the top concern, followed by data security and privacy, as well as reliability of gen AI responses. The problem, however, is as much a scale problem as it is a cost problem, Perlov says. In many cases, organizations launch ambitious AI projects that may be expensive to scale up when small and strategic initiatives may lead to quicker returns, he says. “Some [CIOs] are playing around with technology, and they’re seeing cool things, and it’s not part of a strategy, and then they want to scale it up,” he says. “And often, it doesn’t scale up, either because they didn’t calculate it upfront, or they used an extremely expensive method to do it, like there are easier ways to achieve this, or cheaper ways.” source

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Agentic AI: 6 promising use cases for business

With AI agents popping up in so many situations and platforms, organizations interested in the technology may find it difficult to know where to start. A handful of use cases have so far risen to the top, according to AI experts. Agentic AI will integrate smoothly with ERP, CRM, and business intelligence systems to automate workflows, manage data analysis, and generate valuable reports, says Rodrigo Madanes, global innovation AI officer at EY, a consulting and tax services provider. AI agents, unlike some past automation technologies, can make decisions in real-time, making process automation a primary use case. “AI agents can automate repetitive tasks that previously required human intervention, such as customer service, supply chain management, and IT operations,” Madanes says. “What sets the technology apart is its ability to adapt to changing conditions and handle unexpected inputs without manual oversight.” source

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A blueprint for successfully executing business-aligned IT strategies

CIOs must take an active role in educating their C-suite counterparts about the strategic applications of technologies like, for example, artificial intelligence, augmented reality, blockchain, and cloud computing. By bridging the gap between technical complexity and business relevance, CIOs can ensure that technology initiatives align with core business objectives, focusing on real-world applications rather than theoretical use cases. This practical understanding of technology enables businesses to make informed decisions, balancing the potential benefits of innovation with the realities of implementation and scalability.  Adopting agile methodologies for flexibility and adaptation  The Greek philosopher Heraclitus famously stated, “Change is the only constant.” John Kotter, a professor at Harvard Business School and a renowned change expert, introduced an eight-step change process in his 1995 book, “Leading Change.” In today’s business environment, agile methodologies have become indispensable for maintaining alignment between IT and business strategies. Agile practices allow organizations to remain flexible, adjusting projects and initiatives in response to evolving market conditions and customer feedback.  By implementing agile methodologies, CIOs ensure IT projects are delivered in short, manageable cycles, enabling continuous adjustments based on real-time data and feedback. This iterative approach fosters collaboration across departments and requires a company culture that embraces agility and constant change. Ensuring the cultural fit with agile principles is critical for promoting an environment where change is welcomed and harnessed for growth. For example, a financial institution might launch a new digital platform and continuously refine its features based on user feedback, showcasing how agile culture and iterative processes efficiently meet both IT and business objectives. Such a dynamic culture ensures that the organization remains flexible and adaptable in an ever-evolving digital landscape. source

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What underscores, and undermines, a successful CIO-CEO collaboration

Regardless, open communication is essential, says Pereyra, who advocates constant dialogue that helps align expectations and address concerns. “We’re bombarded by technologies that always arrive with the promise of revolutionizing all sectors,” he says. “So it’s our responsibility to rationalize all this information, give visibility to the company and its business areas of what these solutions can provide, and, more specifically, what is applicable to the company.”  He adds the importance of maintaining a customer-centric approach, “to align our efforts with their needs,” considering that circumstances change quickly, and being willing to adapt is essential to staying relevant.  If communication is key, then patience and long-term planning are equally vital, according to Cossio, when it comes to digital transformation projects. “You have to have a clear roadmap, with short-, medium-, and long-term objectives, and be aware there will be times when progress won’t be as fast as desired,” she says. There’s also the need to recognize this isn’t just a technological change, but a cultural change. Flexibility is essential to not only help manage technology, but drive growth and innovation. With this adoption of a new way of working, driven by digital tools, the role of the CIO and the relationship with the CEO, are irreversibly intertwined. source

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Global AI regulations: Beyond the U.S. and Europe

An earlier article described emerging AI regulations for the U.S. and Europe. Building on that perspective, this article describes examples of AI regulations in the rest of the world and provides a summary on global AI regulation trends. First, although the EU has defined a leading and strict AI regulatory framework, China has implemented a similarly strict framework to govern AI in that country. Second, some countries such as the United Arab Emirates (UAE) have implemented sector-specific AI requirements while allowing other sectors to follow voluntary guidelines. Lastly, voluntary frameworks have been proposed by many countries such as Singapore and Japan, to encourage AI innovation. The G7 collection of nations has also proposed a voluntary AI code of conduct. India has avoided any commitment to AI regulations, at this time relying on existing legislation that protects personal digital privacy, an example that many other countries are following. The complexity of varying global AI regulations is challenging for CIOs. Indeed, as IDC reported in a earlier this year, the U.S. has a complex web of differing state laws regarding AI (Navigating the Fragmented U.S. AI and GenAI Regulatory Landscape, IDC, July 2024). The complexity increases for CIOs that operate in a global environment, where national regulations span the spectrum from detailed and prescriptive such as in the EU or China, to voluntary or non-existent, such as India. China follows the EU, with additional focus on national security In March 2024 the Peoples Republic of China (PRC) published a draft Artificial Intelligence Law, and a translated version became available in early May. The Law provides a set of frameworks that are as comprehensive as the EU AI Act, with the intention of balancing the need for innovative AI development with the need to safeguard society. Importantly, where the EU AI Act identifies different risk levels, the PRC AI Law identifies eight specific scenarios and industries where a higher level of risk management is required for “critical AI.” The identified scenarios where AI is used include judicial, news, medical, biometric recognition, autonomous driving, social credit, social bots and where AI is used by state organizations. This allows for more rapid and targeted legislation when needed. Lastly, China’s AI regulations are focused on ensuring that AI systems do not pose any perceived threat to national security. The UAE provides a similar model to China, although less prescriptive regarding national security. UAE has proactively embraced AI, to both foster innovation while providing secure and ethical AI capabilities. In particular, the UAE AI Office created an AI license requirement for applications in the Dubai International Finance Centre. Further, the Dubai Health Authority also requires AI license for ethical AI solutions in healthcare. The G7 AI code of conduct: Voluntary compliance In October 2023 the Group of Seven (G7) countries agreed to a code of conduct for organizations that develop and deploy AI systems. The code of conduct is directed by 11 guiding principles, many of which focus on risks, vulnerabilities, security, and protections. As well, the principles address the need for accountability, authentication, and international standards. The G7 leaders directed their national ministers to implement the code of conduct, stressing the need to maximize the benefits of AI while mitigating its risks. However, notably absent from the code is any form of enforcement or penalty; compliance is completely voluntary. Similar voluntary guidance can be seen in Singapore and Japan. Singapore emphasizes AI innovation particularly in the financial sector, with no specific set of AI regulations. The government continues its emphasis on protection of digital privacy as a mechanism for controlling inappropriate AI. Japan has taken a slightly different approach, with two directions: voluntary guidelines for all industries and “sector-specific restrictions on large platforms to safeguard the use of AI” (Navigating the AI Regulatory Landscape: Differing Destinations and Journey Times Exemplify Regulatory Complexity, IDC, March 2024). The rest of the world: Light-touch or non-existent AI regulations India provides a model of how the rest of the world approaches AI, which aligns with the G7 model of voluntary compliance. As described by Carnegie Endowment for International Peace, India has a “light touch approach to AI regulation,” with a model that strikes a balance between innovation and safety while not delaying the country’s steady progress toward a growing and profitable digital economy. While India has multiple laws and regulations regarding electronic data and protection of digital privacy (e.g., the Information Technology Act of 2000), a single AI responsibility or a focused AI act such as that of the EU, does not exist. Recognizing the global economic importance of AI, India’s approach is to encourage AI development while monitoring AI usage to prevent societal abuse. For many countries in the world, AI is recognized as economically important yet is dominated by the U.S. and countries of the EU. Innovation is seen as key to societal and economic improvement, with AI leading the list of innovation levers. Regulations are sometimes seen as a hindrance to innovation, and many jurisdictions will wait and watch for global consensus to emerge on AI regulations. Unfortunately for CIOs, the global AI regulatory map will continue to be incomplete and uneven with developments occurring asynchronously in various countries. As IDC points out in a review of 11 jurisdictions, each country begins with a different set of goals, a different destination, and a variety of timelines for AI regulation (Navigating the AI Regulatory Landscape: Differing Destinations and Journey Times Exemplify Regulatory Complexity, IDC, March 2024). However, for the larger jurisdictions, such as the UK, EU or China, and some of the United States, CIOs must pay attention to established and emerging AI regulations and the probability of government enforcement. This is an unexpected new role for CIOs, but offers an opportunity for leadership in a fast-developing and complex global environment. Learn more about IDC’s research for technology leaders OR subscribe today to receive industry-leading research directly to your inbox. International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for

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Shortsighted CEOs leave CIOs with increasing tech debt

Some IT leaders, however, aren’t convinced about the IBM report’s focus on IT shortcuts vs. innovation. IT spending is driven more by a desire to enable business goals, such as growth, and managing risks, including cyberattacks, says Yvette Kanouff, partner at JC2 Ventures, a tech-focused venture capital firm. “These objectives might require short-term IT spending to help the business achieve its goals, but it’s not a trade-off,” she says. “It delivers results.” Still, there is some tension between short-term and long-term goals, because every organization has a backlog of IT tasks that need attention, she adds. “While it’s important to address the backlog, continuously focusing on cleanup can get in the way of forward progress,” Kanouff says. “This is why it’s essential to balance short-term and long-term objectives.” source

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Meta creates ‘Business AI’ group led by ex-Salesforce AI CEO Clara Shih

Keeping control However, anyone wanting to use the latest Llama 3.2 model must agree to a 630-word acceptable use policy that, for example, excludes its use by governments in national security roles unless Meta grants permission, as it did recently to the US government. Meta also has a veto on competitors using Llama for anything too big: The Llama 3.2 license also requires that enterprises offering services to more than 700 million monthly active users must request an additional license from Meta, “which Meta may grant … in its sole discretion” and may not use the software until Meta expressly allows it. Since Meta licenses each of its AI models separately there’s nothing stopping it from lowering that threshold for future versions to bring more applications for the software under its control or demanding financial compensation for broader usage licenses. source

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How Trump’s appointment of Brendan Carr as FCC chairman will affect enterprises

Reining in big tech This is less about regulation per se than liking some regulations and interventions more than others. Reading Carr’s public statements as FCC commissioner — he also authored the new administration’s ‘Project 2025’ section on the FCC — a variety of attention-grabbing opinions stand out. He’s a critic of what he claims are attacks on free speech by big tech platforms. As he put it on X (formerly Twitter) last week in the same context, “the censorship cartel must be dismantled.” An obvious counter to that view is that consumers can choose to go elsewhere if they dislike a platform’s content moderation policy. This, of course, includes Trump’s Truth Social or Musk’s Twitter, with the latter recently losing users to its smaller rival Bluesky, in part for precisely this reason. His other positions include supporting a recent new law banning TikTok unless its Chinese parent sells the US business, and supporting the expansion of broadband access through Elon Musk’s SpaceX Starlink satellite network. source

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