Generative AI (aka, GenAI) is becoming democratized by the confluence of massively pre-trained models, cloud computing, and open source -- making these models accessible to workers worldwide. By 2026, Gartner predicts, over 80% of enterprises will have used GenAI APIs and models and/or deployed GenAI-enabled applications in production environments, up from less than 5% in early 2023.
The democratization of access to AI has made the need for AI Trust, Risk and Security Management (TRiSM) more clear and urgent. Without guardrails, AI models can rapidly generate compounding negative effects that spin out of control, overshadowing any positive performance and societal gains that AI enables. AI TRiSM provides tooling for ModelOps, proactive data protection, AI-specific security, model monitoring (including monitoring for data drift, model drift, and/or unintended outcomes), and risk controls for inputs and outputs to third-party models and applications. Gartner predicts that by 2026, enterprises that apply AI TRiSM controls will increase the accuracy of their decision-making by eliminating up to 80% of faulty and illegitimate information.
3. AI-Augmented Development
AI-augmented development is the use of AI technologies, such as GenAI and machine learning, to aid software engineers in designing, coding, and testing applications. AI-assisted software engineering improves developer productivity and enables development teams to address the increasing demand for software to run the business. These AI-infused development tools enable software engineers to spend less time writing code, so they can spend more time on strategic activities such as the design and composition of compelling business applications.
Intelligent applications include intelligence -- which Gartner defines as learned adaptation to respond appropriately and autonomously -- as a capability. This intelligence can be utilized in many use cases to better augment or automate work. As a foundational capability, intelligence in applications comprises various AI-based services, such as machine learning, vector stores, and connected data. Consequently, intelligent applications deliver experiences that dynamically adapt to the user.
5. Augmented-Connected Workforce
The augmented-connected workforce (ACWF) is a strategy for optimizing the value derived from human workers. The need to accelerate and scale talent is driving the ACWF trend. The ACWF uses intelligent applications and workforce analytics to provide everyday context and guidance to support the workforce's experience, well-being, and ability to develop its own skills. At the same time, the ACWF drives business results and positive impact for key stakeholders. Through 2027, 25% of CIOs will use ACWF initiatives to reduce time to competency by 50% for key roles.
6. Continuous Threat Exposure Management
Continuous threat exposure management (CTEM) is a pragmatic and systemic approach that allows organizations to evaluate the accessibility, exposure, and exploitability of an enterprise's digital and physical assets continually and consistently. Aligning CTEM assessment and remediation scopes with threat vectors or business projects, rather than an infrastructure component, surfaces not only the vulnerabilities but also the unpatchable threats. By 2026, Gartner predicts that organizations prioritizing their security investments based on a CTEM program will realize a two-thirds reduction in breaches.
7. Machine Customers
Machine customers (also called 'custobots') are nonhuman economic actors that can autonomously negotiate and purchase goods and services in exchange for payment. By 2028, 15 billion connected products will exist with the potential to behave as customers, with billions more to follow in the coming years. This growth trend will be the source of trillions of dollars in revenues by 2030 and eventually become more significant than the arrival of digital commerce. Strategic considerations should include opportunities to either facilitate these algorithms and devices, or even create new custobots.
8. Sustainable Technology
Sustainable technology is a framework of digital solutions used to enable environmental, social, and governance (ESG) outcomes that support long-term ecological balance and human rights. The use of technologies such as AI, cryptocurrency, the Internet of Things and cloud computing is driving concern about the related energy consumption and environmental impacts. This makes it more critical to ensure that the use of IT becomes more efficient, circular, and sustainable. In fact, Gartner predicts that by 2027, 25% of CIOs will see their personal compensation linked to their sustainable technology impact.
Platform engineering is the discipline of building and operating self-service internal development platforms. Each platform is a layer, created and maintained by a dedicated product team, designed to support the needs of its users by interfacing with tools and processes. The goal of platform engineering is to optimize productivity and the user experience, and to accelerate the delivery of business value.
10. Industry Cloud Platforms
By 2027, Gartner predicts, more than 70% of enterprises will use industry cloud platforms (ICPs) to accelerate their business initiatives, up from less than 15% in 2023. ICPs address industry-relevant business outcomes by combining underlying SaaS, PaaS, and IaaS services into a whole product offering with composable capabilities. These typically include an industry data fabric, a library of packaged business capabilities, composition tools, and other platform innovations. ICPs are tailored cloud proposals specific to an industry and can further be tailored to an organization's needs.
In addition to the top technology strategic trends, Gartner also provided its top strategic IT predictions, exploring how GenAI has changed executive leaders' way of thinking on every subject and how to create a more flexible and adaptable organization that is better prepared for the future. Here are Gartner's top 10 strategic predictions:
By 2027, the productivity value of AI will be recognized as a primary economic indicator of national power.
By 2027, GenAI tools will be used to explain legacy business applications and create appropriate replacements, reducing modernization costs by 70%.
By 2028, enterprise spending on battling malinformation will surpass $30 billion, cannibalizing 10% of marketing and cybersecurity budgets to combat a multifront threat.
By 2027, 45% of chief information security officers (CISOs) will expand their remit beyond cybersecurity, due to increasing regulatory pressure and attack surface expansion.
By 2028, the rate of unionization among knowledge workers will increase by 1,000%, motivated by the adoption of GenAI.
In 2026, 30% of workers will leverage digital charisma filters to achieve previously unattainable advances in their careers.
By 2027, 25% of Fortune 500 companies will actively recruit neurodivergent talent across conditions like autism, ADHD, and dyslexia to improve business performance.
By 2028, there will be more smart robots than frontline workers in manufacturing, retail, and logistics due to labor shortages.
By 2026, 50% of G20 members will experience monthly electricity rationing, turning energy-aware operations into either a competitive advantage or a major failure risk.
By 2026, generative AI will significantly alter 70% of the design and development effort for new web applications and mobile apps.
Research from Salesforce's annual State of IT report confirms many of the projections from Gartner. Many other independent research reports validate the accelerated adoption of AI, including generative AI. According to McKinsey, 50% of organizations used AI in 2022. IDC is forecasting global AI spending to increase by a staggering 26.9% in 2023 alone. A recent survey of customer service professionals found adoption of AI had risen by 88% between 2020 and 2022. Customer service leads AI use cases with organizations with AI using it in the following ways: service operations optimization (24%), new AI-based products (20%), customer service analytics (19%), customer segmentation (19%), AI-based product enhancements (19%), customer acquisition and lead generation (17%), contact center automation (16%), and product feature optimizations (16%).
The State of IT report found that generative AI has only recently become mainstream. The report shows 86% of IT leaders believe generative AI will have a prominent role in their organizations in the near future. Yet 64% of IT leaders are concerned about the ethics of generative AI, and 62% are concerned about its impacts on their careers. The report also notes that ethics and generative AI focus on accuracy, bias, toxicity, safety, and privacy.
In a recent survey of IT leaders, concerns around generative AI included security risks (79%), bias (73%), and carbon footprint (71%). With nearly 9 out of 10 IT leaders believing generative AI will have a prominent role in their organizations in the near future, business leaders must understand the strategic technology trends highlighted by Gartner for 2024 and beyond. In order to do this, businesses must commit to education, stakeholder reskilling, and strategic partnerships in order to ready themselves for a future that is led by AI-powered products and services.