Artificial Intelligence is poised to reshape the IT industry and the way business is conducted. This new forecast comes from market intelligence firm IDC, which predicts that enterprise spending on generative AI (GenAI) from now to 2027 will be 13 times the growth rate of overall global IT spending.
IDC forecast Enterprise spending on GenAI services, software and infrastructure will grow from $16 billion in 2023 to $143 billion in 2027. Spending on generative AI is expected to reach a compound annual growth rate (CAGR) of 73.3% over the four-year period to 2027.
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To help organizations better understand how to leverage GenAI technology for business success, IDC has developed a new framework – the Generative AI Path to Impact – that explains the key activities and elements along the path.
Before exploring any of GenAI’s core technologies, IDC believes the following core activities need to be established:
Establish a responsible AI policy: This must include fairness, transparency, security, and accountability regarding the data used to train the models, as well as defined policies on how the results are used. A responsible AI policy should provide clarity on the roles and responsibilities of developers, users and other stakeholders when dealing with legal and compliance issues.
Create an AI strategy and road map: A set of defined, measurable, and prioritized GenAI use cases is needed to align the organization to the core areas that will deliver the greatest business impact in the short, medium, and long term.
Design an Intelligence Architecture: It is important to manage the lifecycle and governance of data, models and business contexts for each use case. The architecture should include protocols for data privacy, security and intellectual property protection.
Re-skilling and training personnel: Creating and using GenAI models will require new skills, such as prompt engineers to write and test prompts for GenAI systems. Each organization must create a new competency map for core AI technologies and business capabilities to deploy GenAI at scale across the organization. Organizations should also develop personalized training programs for key roles.
The next step in defining GenAI impact pathways is prioritizing an identified set of use cases. IDC defines a use case as a business-financed initiative enabled by technology that delivers a measurable result. There are three broad types of GenAI use cases that need to be evaluated:
Industry: This involves more custom work and, in some cases, companies may need to develop their own GenAI models. Examples include generative material design for generative drug discovery and manufacturing in the life sciences. Specialized use cases are built around specific models and model providers, with custom integration architectures designed for individual clients.
Business Functions: These use cases typically involve integrating a model (or multiple models) with corporate data for use by specific departments or business functions such as marketing, sales, and procurement. Many organizations are already testing such use cases but are concerned about intellectual property leaks and data governance.
joy: These use cases are aligned with work tasks, such as summarizing reports, creating job descriptions, or generating Java code. Adding GenAI functionality to existing applications to improve productivity, such as Microsoft 360 Copilot or Duet AI for Google. In many of these use cases, business value can be delivered through content and data that has been pre-trained on the underlying base models.
IDC recommends adopting a “Three Horizons” Framework to help organizations transform their business models using GenAI.
- Horizon 1 focuses on near-term, incremental innovation.
- Horizon 2 focuses on disruptive innovation in the medium term.
- Horizon 3 focuses on long-term business model transformation.
The framework drives alignment across all business domains and helps prioritize key initiatives.
IDC’s predictions for 2024 focus largely on the emergence of AI as a major turning point in the technology industry. “Every IT provider will incorporate AI into the core of their business, investing money, brainpower and time,” he said Rick Villars, group vice president, global research at IDC. Here’s IDC’s 2024 Global IT industry top ten forecast:
1. Core IT Shift: IDC expects the shift in IT spending toward AI to be rapid and dramatic, affecting nearly every industry and application. By 2025, Global 2000 companies will allocate more than 40% of their core IT spending to AI-related initiatives, leading to double-digit growth in product and process innovation rates.
2.IT Industry AI Pivot: The IT industry will feel the impact of the AI watershed more than any other industry, as every company races to launch AI-enhanced products/services and help their customers implement AI. For most, AI will replace the cloud as the main driver of innovation.
3. Structural disturbances: AI spending rates will be constrained by 2025 for many enterprises due to large workloads and resource shifts in corporate and cloud data centers. Uncertainty about silicon supply will be compounded by shortcomings in networking, facilities, model confidence and AI capabilities.
4. Great Data Grab: In an AI everywhere world, data is a critical resource, which feeds AI models and applications Technology providers and service providers recognize this and will accelerate investments in additional data assets that they believe will improve their competitive position.
5. IT Skill Mismatch: Inadequate training in AI, cloud, data, security and emerging technology areas will directly and negatively impact enterprise efforts to succeed in efforts dependent on such technologies. By 2026, underfunded efficiency initiatives will prevent 65% of enterprises from achieving full value from those technology investments.
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6. Transformation of Service Industry: GenAI will revolutionize human-provided services for strategy, change and training. By 2025, 40% of services will involve GenAI-enabled delivery, impacting everything from contract negotiations to IT Ops to risk assessment.
7. Integrated Control: One of the most challenging tasks for IT teams over the next few years will be navigating the maturity of control platforms as they move from addressing a few basic systems to a standard platform that manages operations across infrastructure, data, AI services and business applications. /process.
8. Converged AI: Today’s fascination with GenAI should not delay or derail existing or other AI investments. Organizations must envision, test, and produce fully integrated AI solutions that allow them to solve new use cases and customer personas at significantly lower price points.
9. Local Experience: Accelerated adoption of Gen AI will enable organizations to enhance their edge computing use cases with relevant experiences that better align business outcomes with customer expectations.
10. Digital High Frontier: Satellite-based Internet connectivity will deliver broadband everywhere, help bridge the digital divide, and enable a host of new capabilities and business models. By 2028, 80% of enterprises will integrate LEO satellite connectivity, creating a unified digital service fabric that ensures resilient ubiquitous access and guarantees data fluidity.