The great acceleration: CIO perspectives on generative AI

The process would start with an overhaul of large on-premises or on-cloud applications and platforms, focused on migrating everything to the latest tech architecture. Only once those upgrades were completed – an exercise that typically took three to five years and hundreds of millions of dollars – could individual business units start re-working their systems and processes based on the new architecture. Another finding shows that organizations are looking to leverage open source technology to build their own custom LLMs. CIOs recognize the risks third-party services represent for maintaining data security and privacy with their company data.

Play the long game and create ‘option value’

If you’re not investing for both the short and long term, you’re designing for obsolescence. Millennials and Gen Z are now the dominant generations, bringing new expectations for purpose, collaboration, and digital fluency. At the same time, low-code/no-code platforms, citizen developers, and ubiquitous AI tools are decentralizing engineering and tech expertise. It took 40 years for most Americans to adopt electricity at home, 20 years for half the population to adopt smartphones, and 10 months for half the global workforce to adopt GenAI. The fastest adoption rate in history means the consumer is changing rapidly, becoming more informed, empowered, and discerning.

Accelerate change with Value Stream Management

To cut through the froth, CIO.com polled a range of IT leaders and experts for their views on where we are with generative AI, their hopes and their concerns. Laurel Ruma, global director of custom content for MIT Technology Review says establishing these frameworks can help organizations navigate the potential risks and maximize the benefits of generative AI adoption. Data infrastructure is another consideration, as generative AI requires flexible, scalable, and compute-efficient systems. CIOs and technical leads are embracing different data infrastructures like data lakehouses that can democratize access to data and analytics, enhance security, and combine low-cost storage with high-performance querying, the report said. To keep it simple, generative AI is where computer algorithms are used to generate responses that resemble human-created content, in the form of text, images, graphics, music, computer code or more. The foundational AI models powering these outputs learn from training data that informs and shapes the results.

Learning Tools

Cross-departmental information sharing needs to become the norm for effective AI usage. After all, when a GenAI model is trained on the vast amounts of data and historical insights that exist across an entire organization, it can provide intelligent recommendations and automate repetitive tasks. This can hugely reduce the cognitive load of time-intensive processes, such as incident resolution.

By harnessing the power of Generative AI in ERP systems, businesses can enhance their operational efficiency, optimize decision-making processes, leverage predictive algorithms, and unlock new possibilities for automation and data analysis. Generative AI will increase business agility, connecting dots across the organization to identify and recommend process efficiencies and deliver new insights. Often time-consuming and research-intensive, commercial underwriting can be invigorated by ChatGPT’s mathematical models. As one of the world’s largest payment technology companies, Visa’s embrace of generative AI is a strong indicator of the technology’s transformative potential. With its focus on responsible innovation, data privacy, and collaboration with key stakeholders, Visa is well-positioned to lead the charge in leveraging generative AI to create a more efficient, secure, and inclusive payments ecosystem. Under Hobson’s leadership, Visa is poised to be at the forefront of this technological revolution, paving the way for a more connected, secure, and inclusive financial world.

Privacy issues, intellectual property protection and the still-changing legal rules around AI development and use are all considerations that would-be business users of generative AI must address. And in terms of intellectual property risks, IDC’s Ward-Dutton says oganizations’ own IP can leak into the public domain if they aren’t careful when using public generative AI services. “CIOs play a pivotal role in ensuring ethical and responsible AI practices, striking the right balance between innovation and compliance. With the democratization of AI and the integration of generative models into organizational workflows, we are witnessing the transformative power of AI on a truly enterprise-wide scale,” Ruma said. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a powerful ecosystem of industry-leading digital media brands, with a reach of 15+ million elite tech professionals.

• It’s important to note here that generative AI today is a content development engine.
• CIOs are already cognizant of the limitations and risks of third-party services, including the release of sensitive intelligence and reliance on platforms they do not control or have visibility into.
• Only once those upgrades were completed – an exercise that typically took three to five years and hundreds of millions of dollars – could individual business units start re-working their systems and processes based on the new architecture.
• We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.

However, what’s often overlooked is its capacity to ignite a cultural evolution within organizations. As businesses embrace AI, mindsets can shift from a focus solely on operational efficiency to ones that value creativity and innovation. By removing artificial barriers to a centrally controlled tech architecture, it is possible for every single business unit owner to implement AI-powered solutions and start iterating and transforming their workflows immediately. We are now entering the next innovation cycle driven by Generative AI, a powerful technology with potential far beyond the already impressive capabilities we see today. Like the revolution in cloud technology, the closer AI is to a business’ processes, the more transformative it will be.

Is Vietnam the next source for CIO inspiration?

With the shift in interaction styles, users can simply ask questions and receive instant responses. Certain parallels exist between the emergence of generative AI and the advent of the World Wide Web. Much like the internet disrupted traditional business models and paved the way for the digital era, AI is now changing how we consume content and interact with technology. The organizations that rise to the occasion will be led by an innovative class of CIOs who embrace bold thinking, stay ahead of the market, and build a visionary future. The new CIO lights the way forward with eight critical leadership shifts that will define the success of the AI era.

• Some organizations seek to leverage open-source technology to build their own LLMs, capitalizing on and protecting their own data and IP. CIOs are already cognizant of the limitations and risks of third-party services, including the release of sensitive intelligence and reliance on platforms they do not control or have visibility into. They also see opportunities around developing customized LLMs and realizing value from smaller models. The most successful organizations will strike the right strategic balance based on a careful calculation of risk, comparative advantage, and governance.• Automation anxiety should not be ignored, but dystopian forecasts are overblown.

AI Transformation Beyond The Surface

To ensure this is approached effectively, below are a few considerations for organizations looking to visualize a mental model. Generative AI’s potential for fostering inclusivity is often hidden beneath the surface. It has the power to break down barriers, making information and services more accessible to individuals with disabilities and those in underserved communities. According to Forrester, investment in AI software will grow 50% faster than the wider software market. A recent PagerDuty survey also found that 71% of businesses are looking to expand investments in AI and machine learning (ML) in the next year. This rapid investment in, and expansion of, AI tools within businesses poses a particular headache to CIOs, who must ensure that everyone in the organization uses AI in a compliant way.

The moon landing succeeded with imperfect technology because of the vision, innovation, and resilience of the people behind it. AI has the potential to transform industries, advance science and medicine, and solve some of the world’s most wicked problems. Invest today in the data ecosystems, ethical frameworks, and scalable architectures that will unlock AI’s exponential value over the next decade.

• As businesses embrace AI, mindsets can shift from a focus solely on operational efficiency to ones that value creativity and innovation.
• It can be used to write code, design products, create marketing content and strategies, streamline operations, analyze legal documents, provide customer service via chatbots and even accelerate scientific discovery.
• AI represents not just a technological advancement but a paradigm shift for the cybersecurity community.
• But, as with any big new wave, there is a risk of once-promising projects being washed up and there are clear and obvious concerns over governance, quality and security.
• However, as GenAI matures and businesses move deeper into enterprise-level adoption, it’s become clear that the most transformative impact of GenAI will be on the very idea of transformation itself.

This lighthouse beams light across the organization, helping to navigate barriers and ensuring that AI-driven services are accessible to all, irrespective of abilities or location. Visualize the organization as a “societal nexus.” It interacts with the wider community, recognizing that its AI-powered innovations have broader societal implications. This nexus is a two-way bridge, addressing societal concerns while also providing inclusivity and accessibility. While the business implications of AI are apparent, its impact on society at large is equally significant. As AI technologies become more pervasive, they bring forth profound societal changes, ranging from shifts in employment dynamics to redefining the boundaries of privacy.