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Developers unimpressed by the early returns of generativeAI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts. That’s what we call an AI software engineering agent.
Despite the many concerns around generativeAI, businesses are continuing to explore the technology and put it into production, the 2025 AI and Data Leadership Executive Benchmark Survey revealed. Last year, only 5% of respondents said they had put the technology into production at scale; this year 24% have done so.
What are we trying to accomplish, and is AI truly a fit? ChatGPT set off a burst of excitement when it came onto the scene in fall 2022, and with that excitement came a rush to implement not only generativeAI but all kinds of intelligence. And the tech side of the house should push to make sure theres clarity on this.
Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.
GenerativeAI is revolutionizing how corporations operate by enhancing efficiency and innovation across various functions. Focusing on generativeAI applications in a select few corporate functions can contribute to a significant portion of the technology's overall impact.
CIOs should return to basics, zero in on metrics that will improve through gen AI investments, and estimate targets and timeframes. Set clear, measurable metrics around what you want to improve with generativeAI, including the pain points and the opportunities, says Shaown Nandi, director of technology at AWS.
The launch of ChatGPT in November 2022 set off a generativeAI gold rush, with companies scrambling to adopt the technology and demonstrate innovation. Legacy chatbots, product recommendation engines, and several other useful tools may rely only on earlier forms of AI.
Whether summarizing notes or helping with coding, people in disparate organizations use gen AI to reduce the bind associated with repetitive tasks, and increase the time for value-acting activities. Generally, I’d say we should be really excited about gen AI,” says Cynthia Stoddard, CIO at Adobe.
Most CIOs and CTOs are bullish on agentic AI, believing the emerging technology will soon become essential to their enterprises, but lower-level IT pros who will be tasked with implementing agents have serious doubts. There arent a lot of places to learn about agents now, other than hands-on experience, he adds.
But a substantial 23% of respondents say the AI has underperformed expectations as models can prove to be unreliable and projects fail to scale. So for all its vaunted benefits to efficiency, gen AI doesn’t always reduce workloads. That means AI output will require additional oversight, review, editing, correction, or re-work.
GenerativeAI has been hyped so much over the past two years that observers see an inevitable course correction ahead — one that should prompt CIOs to rethink their gen AI strategies. Operating profit gains from AI doubled to nearly 5% between 2022 and 2023, with the figure expected to reach 10% by 2025, she adds.
For generativeAI, a stubborn fact is that it consumes very large quantities of compute cycles, data storage, network bandwidth, electrical power, and air conditioning. Infrastructure-intensive or not, generativeAI is on the march. of the overall AI server market in 2022 to 36% in 2027.
Increasingly, however, CIOs are reviewing and rationalizing those investments. Theres a renewed focus on on-premises, on-premises private cloud, or hosted private cloud versus public cloud, especially as data-heavy workloads such as generativeAI have started to push cloud spend up astronomically, adds Woo. Judes Perry.
IT leaders looking for a blueprint for staving off the disruptive threat of generativeAI might benefit from a tip from LexisNexis EVP and CTO Jeff Reihl: Be a fast mover in adopting the technology to get ahead of potential disruptors. But the foray isn’t entirely new. We will pick the optimal LLM. We use AWS and Azure.
Chieftechnologyofficers are key players in the enterprise C-suite, oftentimes working in collaboration with CIOs at the forefront of new and innovative technologies. They are among the most important hires organizations are making today due to the business value that successful technology deployments can bring.
GenerativeAI offers great potential as an interface for enabling users to query your data in unique ways to receive answers honed for their needs. For example, as query assistants, generativeAI tools can help customers better navigate an extensive product knowledge base using a simple question-and-answer format.
Asure anticipated that generativeAI could aid contact center leaders to understand their teams support performance, identify gaps and pain points in their products, and recognize the most effective strategies for training customer support representatives using call transcripts. Yasmine Rodriguez, CTO of Asure.
To solve the problem, the company turned to gen AI and decided to use both commercial and open source models. Both types of gen AI have their benefits, says Ken Ringdahl, the companys CTO. We picked Metas Llama to be the model of choice due to cost, control, maintainability, and flexibility.
GitHub first launched its copilot in 2021 , and Microsoft 365 Copilot became generally available a few months ago. These AI assistants often use the term copilot to indicate how generativeAI capabilities embedded in workflow tools can augment and assist people in performing tasks and prompting for information more efficiently.
For many organizations, preparing their data for AI is the first time they’ve looked at data in a cross-cutting way that shows the discrepancies between systems, says Eren Yahav, co-founder and CTO of AI coding assistant Tabnine. In the generativeAI world, the notion of accuracy is much more nebulous.”
The impact of generativeAIs, including ChatGPT and other large language models (LLMs), will be a significant transformation driver heading into 2024. Below are several generativeAI drivers for CIOs to consider when evolving their digital transformation priorities.
I started studying art to give myself a break from the high-tech world. Now, ironically, the art world is being disrupted by emerging technology–specifically generativeAI tools such as OpenAI’s ChatGPT, Google’s Bard, and Meta’s LLaMa. GenerativeAI does this based on a knowledge graph, a network of related concepts.
From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. Just a few short years ago, models like GPT-1 (2018) and GPT-2 (2019) barely registered a blip on anyone’s tech radar. Why has agentic AI become the latest rage? Did this need to be an agent?
CIOs are increasing their overall uptake of generativeAI , pushing AI from its current role in isolated pockets of the enterprise into more organization-wide uptake and speeding the adoption of the technology across new industries, a new survey found. Note: This article was written without AI assistance.)
And as reliance on generativeAI rises, the number of APIs in use is anticipated to increase accordingly. But APIs do more than support next-generationtechnologies — they already serve a foundational purpose within most enterprises. Ajay Sabhlok, CIO and CDO at zero trust data security company Rubrik, Inc.,
With the merging of operational efficiency and embracing new technologies, today’s CIOs are under increasing pressure to do more with less and become both technologists and business leaders, says Sunny Azadeh, CIO at digital services company GlobalLogic. “In
Additionally, the cost of cyber disruption will increase next year as businesses experience downtime due to cyberattacks and scramble to implement defenses fit for the AI-enabled attacker era. In 2025, attackers will begin developing and testing generativeAItechnologies to use over the next 3-5 years.
I explored how Bedrock enables customers to build a secure, compliant foundation for generativeAI applications. Now I’d like to turn to a slightly more technical, but equally important differentiator for Bedrock—the multiple techniques that you can use to customize models and meet your specific business needs.
Those same characteristics, however, reveal the risks AI pose to this sector. So business technology leaders in financial services are carefully navigating a path toward AI. AI dominates discourse and headlines, but financial services technology leaders know there’s a lot of substance amid the noise.
The generative artificial intelligence (AI) revolution is in full swing, and customers of all sizes and across industries are taking advantage of this transformative technology to reshape their businesses. To power so many diverse applications, we recognized the need for model diversity and choice for generativeAI early on.
Other respondents said they aren’t using any generativeAI models, are building their own, or are using an open-source alternative. Putting aside the fact this is an astronomically high adoption rate for a brand new technology, it’s also an indicator of how risky this space is. And the AI writing assistant category grew by 177%.
An IBM report based on the survey, “6 blind spots tech leaders must reveal,” describes the huge expectations that modern IT leaders face: “For technology to deliver enterprise-wide business outcomes, tech leaders must be part mastermind, part maestro,” the report says.
And when it comes to business and management IT jobs, 63% were classified as “high transformation” due to AI. And online education company Pluralsight conducted a survey of IT professionals in the US and UK and found that 74% worried AI tools will make many of their daily skills obsolete. I like driving the business forward.”
Tech services provider Logicalis found in its 2024 Global CIO Report that 89% of CIOs reported “actively seeking opportunities to incorporate AI capabilities into their companies,” making it the No. A committee reviews potential projects and expected returns, to ensure the company is pursuing impactful AI initiatives.
When Morgan Stanley announced its new generativeAI support tools for financial advisors last week, it talked about gaining efficiencies from its notetaking abilities. That’s not the goal, at least not today,” the source said, adding that initial efforts will not necessarily be reviewed by corporate. “We
A more operational, business-specific way of leveraging generativeAI is beginning to take shape in the form of AI agents that quietly work behind the scenes, moving beyond gen AI’s creational capabilities toward autonomous decision-making in enterprise workflows.
As a nonprofit R&D center for the US government, MITRE is no stranger to AI. Its researchers have long been working with IBM’s Watson AItechnology, and so it would come as little surprise that — when OpenAI released ChatGPT based on GPT 3.5 We took a risk.
But for a select few, the deeper challenges of departmental technologies being funded, procured, and managed without IT involvement are the missed opportunities to better engage and fulfill departmental technology needs. That’s not to downplay the inherent risks of shadow IT.
If this is one aspect of the future of AI, what will be the implications for technology leaders? In February 2024, Bjorn Jesch, CIO at German asset management and investment firm DWS , posted a video of his own AI-built avatar providing a glimpse of how he saw the market developing in the near- to mid-term.
If you don’t join board meetings often, preparation is paramount, starting with learning about the directors’ backgrounds and reviewing minutes from previous meetings. Be prepared to answer common board questions about cyber readiness, technology roadmaps, and plans to hire and retain a diverse team.
Today, Mixbook is the #1 rated photo book service in the US with 26 thousand five-star reviews. However, the Mixbook Storyarts team sought more granular control over the style and tone of the captions, leading to a diverse team that included an Emmy-nominated scriptwriter reviewing, adjusting, and adding unique handcrafted examples.
2023 was a year made notable by a range of unexpected, unpredictable, and fast-moving challenges that, despite seemingly having little to do with technology, had profound impacts on IT strategies. Delayed decision-making Bhadresh Patel, chief digital officer at global consulting firm RGP, sees organization’s showing more caution than usual.
Mounting technical debt from mission-critical systems CIOs have good reason to stress out over rising technical debt and the impact of supporting legacy systems past their end-of-life dates. Neglecting to address technical debt in a timely manner can lead to catastrophic consequences.”
GenerativeAI is already having an impact on multiple areas of IT, most notably in software development. Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others.
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