The world of data analytics and artificial intelligence (AI) continues to evolve at an unprecedented rate. Over the next four years, analytics, AI, and machine learning developments promise to revolutionize how we interact with technology, unlocking a range of new possibilities.
Analytics and AI trend #1: The integration of generative AI and business intelligence
Traditional business intelligence (BI) vendors need to contend with generative AI’s growing influence. To stay competitive, they’ll need to integrate generative AI capabilities into their tools for more potent and automated BI solutions. This evolution promises to deliver enhanced insights and foster a more intuitive user experience.
The shift towards generative AI for BI
This shift promises numerous opportunities. For starters, generative AI has the potential to autonomously generate insights and narratives from data—automating report and dashboard creation. These insights may unveil previously undiscovered relationships between business processes, leading to newfound efficiencies. Generative AI can also automate data cleansing and preparation, making it easier to access reporting and predictive analysis.
The future of generative AI for BI
As companies move past the novelty of generative AI, they’ll prioritize practical applications that bring tangible value to their operations. Future trends indicate a shift towards more agent-based functionalities, where AI not only provides information but actively performs valuable tasks. Generative AI is also expected to mature in handling various modalities of information—including images, audio, and video—enabling seamless multi-modal interactions.
Analytics and AI trend #2: The maturation and monetization of AI subscriptions
The AI landscape is undergoing a pivotal shift from novelty and experimentation to a phase of commercial pricing and strategic considerations. Recent announcements of OpenText™ Aviator, as well as announcements from other key players in the field, such as OpenAI and Microsoft, provide a glimpse into the emerging commercial pricing models that are set to define the year.
Changing landscape of AI pricing models
The recent moves by OpenAI and Microsoft highlight how AI pricing models are evolving. OpenAI’s reduced prices and Microsoft’s introduction of Microsoft 365 Copilot as a subscription-based service demonstrate the industry’s shift towards cost-effective and subscription-based AI offerings. Businesses are expected to allocate significant budgetary resources to AI subscriptions, especially as more players enter the market, including those in enterprise resource planning (ERP), human resources management (HRM), and customer relationship management (CRM). This raises critical questions about financial commitments, funding, and workforce considerations.
Pragmatic approach to AI subscriptions
The era of AI novelty is coming to an end, requiring businesses to take a more pragmatic and financially conscious approach. They’ll need to carefully evaluate the benefits of AI subscriptions against their financial capacities and strategic goals. Particularly in 2024, as AI subscriptions become more commercialized, enterprises wanting to effectively harness AI’s true value will need to navigate cost, utility, and workforce factors.
Analytics and AI trend #3: ESG initiatives powered by analytics and AI
In the current corporate landscape, there is a growing emphasis on environmental, social, and governance (ESG) principles. The analysis of governance issues, especially those related to ESG, will be crucial in 2024—with the goal of being able to identify and address inefficiencies without adding waste.
Organizations that process information effectively will gain valuable operational insights and be able to reduce carbon emissions through targeted initiatives. For example, companies will monitor and analyze energy usage patterns, identify inefficiencies, and optimize consumption. At the same time, analytics teams will operate on fewer servers to minimize costs and reduce emissions.
Analytics and AI trend #4: Single-pane-of-glass analytics
Analytics today is performed on segmented platforms covering a variety of domains—including traditional business intelligence, IoT analytics, AIOps, predictive analytics, in-database machine learning, and generative AI. However, this separation often creates data silos, increasing storage costs and raising data security concerns. To address these challenges, organizations will turn to single-pane-of-glass analytics.
This solution unifies data and interfaces from multiple sources, providing a comprehensive view of the organization’s analytics landscape. It accommodates diverse analytical forms and enables different teams to work within their dedicated workspaces—without interference. Moving forward, analytics users will need a unified platform to seamlessly access and analyze data, regardless of their analytical style. Embracing the single-pane-of-glass analytics approach allows informed decision-making by unlocking your data’s full potential.
What will we see less of in 2024 for AI and analytics?
The COVID-19 pandemic greatly impacted the workplace and software development, influencing various aspects. As we move forward, certain developments are expected to bring about changes:
- Reduced workgroup silos: Remote work has transformed team collaboration, even as we transition back to physical offices. Collaboration tools like Teams, Zoom, and Slack are breaking down barriers between different groups and fostering improved communication.
- Decline of traditional businesses: The pandemic emphasized digital transformation, compelling companies to incorporate digital tools and cloud-based technologies, such as cloud-based development platforms and IoT integration. In manufacturing, remote monitoring and predictive maintenance are becoming standard practices. Service-oriented companies are enhancing operational efficiency through digital transformation, gaining insights into routes, schedules, fuel consumption, and maintenance.
- Heightened emphasis on data security: Cybersecurity is a paramount concern in our digitally transformed world. Companies are investing in security measures to protect sensitive data and systems from cyber threats.
These ongoing trends will continue shaping work and software development landscapes.
What’s next for OpenText™ Analytics & AI for 2024?
Our team’s priorities will indeed shift in 2024. This change is primarily driven by generative AI’s growing prominence and its transformative potential in everyday applications. As demonstrated by our launch of OpenText™ Aviator as part of our Cloud Editions release, OpenText has recognized the significant impact that this technology will have on eliminating redundancy and enhancing efficiency across various business roles and industries.
Our approach to analytics and AI extends across many sectors, with the overarching goal of optimizing operations, enhancing customer experiences, and fortifying cybersecurity with AI. Generative AI has been essential to enhancing user-friendliness across diverse industries, and there are several compelling reasons behind its rise in popularity over the past year. Generative AI can streamline and enhance various business roles, freeing human resources to focus on innovation. Developers can automate code development, marketers can craft more effective copy, and help desk services can provide highly accurate automated support.
Learn more about how you can stay at the forefront of analytics and enterprise AI with OpenText.
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