AI, Trust, Risk and Security Management (TRiSM)
Security is a significant concern when using AI models in the system or all across the organization. Also, the increasing availability of AI underscores the importance of managing AI Trust, Risk, and Security, often denoted as TRiSM by Gartner. Without robust safeguards, AI models have the potential to generate escalating adverse outcomes, undermining the positive impacts they could otherwise facilitate.
AI TRiSM encompasses essential tools for Model Operations (ModelOps), proactive data protection and security measures, and comprehensive monitoring of models and data. It also incorporates risk controls, particularly pertinent when utilizing third-party models. According to Gartner’s projections, enterprises adopting AI TRiSM are anticipated to significantly enhance decision-making accuracy, potentially eliminating up to 80% of misleading information by 2026.
Continuous Threat Exposure Management
According to Gartner’s projections, organizations prioritizing security investments guided by a CTEM program are expected to experience a substantial two-thirds reduction in security breaches by 2026.
Continuous Threat Exposure Management (CTEM) represents a systematic methodology enabling organizations to consistently assess and oversee the accessibility, exposure, and exploitation risk associated with their digital and physical assets. By aligning these methodologies with individual projects or threat vectors instead of solely focusing on infrastructure, enterprises can gain a holistic view of vulnerabilities, including those that may be unmatchable.
Gartner anticipates that by 2027, around 25% of CIOs will witness a correlation between their personal compensation and the impact of sustainable technology initiatives.
Sustainable technology involves a set of digital solutions designed to facilitate ESG (Environmental, Social, and Governance) outcomes, fostering a lasting equilibrium in both ecological and human rights aspects. With growing apprehensions about the energy consumption and environmental implications associated with technologies such as AI, cryptocurrency, and cloud computing, organizations are under mounting pressure to enhance the efficiency, circularity, and overall sustainability of their IT practices. Additionally, sustainable technologies provide insights necessary for decision-making and improve overall performance.
Regarding IT organizations, optimizing the developer experience and accelerating business value is the utmost priority. The practice of platform engineering involves building and operating self-service development platforms for internal use. As per the Gartner report, 80% of software engineering organizations will establish platform teams as internal providers of reusable services, components and tools for application delivery.
Also, platform engineering accelerates developer’s abilities to independently run, manage, and develop their applications while ensuring reliability and security.
AI Augmented Development
This pertains to leveraging machine learning, Generative AI, and other AI technologies to support software engineers in application design, coding, and testing tasks. Integrating AI in software development enhances developer efficiency and enables teams to meet growing demands for essential business software. These tools also give engineers more time to focus on strategic activities, such as application design and composition, by automating routine tasks.
Industry Cloud Platforms
It’s a specialized platform for industries that integrates Software-as-a-Service (SaaS), platform-as-a-service (PaaS), and infrastructure-as-a-service (IaaS) elements to deliver a product with customizable features like an industry data fabric a set of business capabilities, and tools for composition. These platforms can be adapted by organizations to suit their particular requirements. According to Gartner, over 70% of enterprises are expected to leverage industry cloud platforms for expediting business initiatives by 2027, a significant increase from the current usage of less than 15%.
Intelligence lies at the core of intelligent applications, as defined by Gartner. It refers to the capacity to autonomously and appropriately respond through learned adaptation. This form of intelligence serves to enhance the efficiency and dependability of automated and augmented tasks, ultimately leading to the delivery of more dynamic user experiences. Technologies like Generative AI can truly make apps more intelligent and transform the experience of customers, users, developers, and owners. Additionally, AI can add predictions and allow organizations to add data-driven decision-making into business processes.
Democratize Generative AI
Enabling widespread access to Generative AI within an organization holds the promise of automating diverse tasks, elevating productivity, cutting costs, and unlocking avenues for growth. This transformative potential extends to reshaping the competitive landscape and altering how enterprises approach their work. The dissemination of information and skills across various roles and business functions is poised to follow, allowing a broad spectrum of individuals to harness the power of Generative AI. Furthermore, business users can easily access and utilize extensive internal and external information sources through natural language conversational interfaces.
Augmented Connected Workforce
The imperative to enhance talent scalability propels the strategy of an Augmented-Connected Workforce (ACWF), designed to maximize the effectiveness of human workers. This approach leverages intelligent applications and workforce analytics to offer guidance and context, fostering a supportive environment for workforce experience, well-being, and skill advancement. The ultimate goal of this approach is to achieve business outcomes and positive stakeholder impact. According to Gartner, by 2027, a minimum of 25% of Chief Information Officers (CIOs) are expected to implement augmented-connected workforce initiatives, aiming to cut the time to competency by 50% for crucial roles.
Gartner has identified a new trend called “custobots,” which are nonhuman entities capable of independently negotiating and purchasing goods and services. They predict that by 2028, there will be 15 billion connected products with custobot capabilities, potentially generating trillions of dollars in revenue by 2030. Gartner advises organizations to consider supporting existing custobots or creating new ones as part of their strategic development.