AI is not a new technology, but enterprises have been investing heavily in predictive and interpretive AI for years, but the GPT-3.5 series announced by OpenAI in late 2022 will capture the world’s attention. , which has triggered a surge in investment in generative AI. I.D.C.
As a result, IDC expects global spending on AI solutions to increase to more than $500 billion in 2027. As a result, most organizations will see a significant shift in the weight of their technology investments toward implementing AI and adopting AI-enhanced products and services.
The explosive global popularity of ChatGPT gave us the first real tipping point in the general adoption of AI. ” Ritu Jyoti, Group VP of Global Artificial Intelligence and Automation Market Research and Advisory Services at IDC. “As investments in AI and automation grow, a focus on outcomes, governance, and risk management will be paramount.”
Diverse regulatory requirements
Accelerated efficiency and catastrophic risk are two sides of the shiny new GenAI coin. To reduce risk, cloud and software platform providers bundle GenAI’s safety and governance packages with their core services to add value and differentiate their services.
Efforts to regulate the adoption and development of AI systems vary by region and country. These varying regulatory requirements may lead organizations to adopt a more gradual approach to AI deployment, which also increases time to value.
Conversations are already emerging as a standard user interface (UI) for both enterprise and consumer applications and solutions. These conversational AI interfaces will have a huge impact on customer engagement, sales, marketing, and even IT help desks.
As the understanding of automation matures, project sponsors are moving from a technology-focused to an outcomes-focused mindset, seeking tangible proof of the value delivered for their investment measured by KPIs aligned to business and financial outcomes. I started asking for it.
Bringing AI to knowledge discovery
Due to the value that GenAI brings to automated testing, IDC believes that GenAI is rapidly changing the software testing landscape, enabling vendors to write a significant proportion of tests, reducing manual effort, and increasing test coverage. We hope that this will lead to improved code quality.
Application Modernization The increased use of AI in IT services will streamline efficiency, increase service delivery speed, and strengthen IT services margins.
The latest advances in generative AI are driving a surge in demand for features like natural language question answering and conversational search that support self-service knowledge discovery.
While technology is a source of advantage, it is business models that can help companies monetize the AI they generate and drive lasting competitive advantage. By 2024, he plans to double the monetization potential of GenAI, with 33% of G2000 companies leveraging innovative business models.
Multiple groups are working towards artificial general intelligence (AGI), and companies plan to experiment with AGI systems by 2028. As AGI evolves, it will be transformative, impacting everything from the labor market to the way we understand concepts like intelligence and creativity.
Until AI workloads that require offloading of tasks from server processors to accelerators are standardized with algorithms and software stacks tailored to server processors, purchasing accelerators (GPUs, FPGAs, AI ASICs and ASSPs) will be This will put pressure on processor (CPU) purchases.