Top 5 Application Priorities for Technology Leaders in 2024
February 28, 2024

As organizations continue to navigate the complexities of the digital era, which has been marked by exponential advancements in AI and technology, the strategic deployment of modern, practical applications has become indispensable for sustaining competitive advantage and realizing business goals. The Info-Tech Research Group report, Applications Priorities 2024, explores the following five initiatives for emerging and leading-edge technologies and practices that can enable IT and applications leaders to optimize their application portfolio and improve on capabilities needed to meet the ambitions of their organizations.

1. Digital Experience

Deliver valuable user, customer, employee, and brand experiences.

At the heart of a modern business strategy, digital experience (DX) refers to the entirety of interactions between a user and an organization through digital products and services. To harness the full potential of DX, the report advises applications leaders to define and build a digital business strategy that prioritizes user, employee, and customer needs.

Key recommendations include focusing on DX and quality in product and service delivery, fostering collaborative delivery practices, and continuously monitoring and managing digital products and services.

Additionally, the selection and delivery of DX technologies, coupled with strong stakeholder, partner, and vendor relationships, is essential for sustaining a dynamic and responsive digital system.

2. Democratized AI

Extend AI access to everyone in the organization.

As AI increasingly becomes an executive priority, the push for its widespread adoption throughout organizations is gaining tremendous momentum. According to the report, 40% of organizations have already invested in AI and ML, and 47% anticipate a positive business impact.

Democratized AI has emerged as a key step in business process automation and an organization's AI journey. This initiative aims to make AI tools accessible to a wide range of organizational members, irrespective of their technical expertise, thereby fostering an inclusive environment for innovation. However, scaled AI implementations come with many challenges that must be addressed to fully realize the benefits of this priority.

In the report, the firm advises applications leaders to identify potential AI use cases and assess the various AI tooling options. By optimizing AI-supporting capabilities and establishing a scalable AI deployment and governance framework, organizations can gradually integrate AI, unlocking its full potential across various business functions.

3. Predictive Solution Management

Predict, prevent, and mitigate solution issues before they happen.

Moving beyond traditional application maintenance, predictive solution management proactively addresses potential issues before they impact operations. This advanced approach uses data analytics, statistical models, and forecasting to anticipate and mitigate future system challenges.

The report recommends applications leaders reinforce their maintenance strategies by assessing the health and technical debt of their applications.

Info-Tech further advises embracing site reliability engineering (SRE) and DevOps methodologies, making IT operations insights widely accessible for broader consumption, and integrating AI within IT operations and applications teams. By adopting these practices, organizations can ensure their applications remain robust, reliable, and aligned with evolving business needs.

4. Multisource Ecosystem

Manage a mutually beneficial ecosystem composed of internally and externally managed solutions and partners.

Info-Tech's report describes this approach as an integrated network of internally and externally sourced technologies. The essence of a multisource ecosystem lies in its ability to foster mutually beneficial relationships among a diverse array of partners, customers, and technology partners.

Multisource ecosystems thrive on the seamless integration of data and workflows across various domains, including departments, tools, systems, customers, suppliers, and external partners. Unlike traditional hierarchical structures, these ecosystems are dynamic, with partnerships that are adaptable and not managed in a manner similar to an integrated organization. They are built on changing and sometimes voluntary partnerships and collaboration among independent entities that can form and break apart suddenly.

To take full advantage of a multisource ecosystem, applications leaders should define and articulate clear goals, develop a sourcing partner strategy, strengthen enterprise integration practices, manage their solution architecture and application portfolio, and foster strong relationships with all stakeholders.

5. Intelligent Solution Delivery

Embed AI into your solution delivery practice.

With mounting demands for high-value solutions amid limited resources and complex environments, embedding AI into solution delivery practices is often viewed as an ideal test pilot. AI's potential to enhance productivity, generate usable test data, and preemptively identify issues positions it as a transformative force within the solution delivery lifecycle (SDLC).

Some of the prominent AI applications that are making strides in the field include synthetic data generation, automated code creation, defect forecasting and debugging, and UI design and prototyping, as well as requirements documentation and elicitation.

The firm recommends that applications leaders focus on optimizing their SDLC practice and explore different AI and automated SDLC tools to elevate their solution delivery frameworks this year.

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