Last week, the Gartner Data & Analytics Summit showcased the evolving landscape of artificial intelligence (AI) and what data leaders, and the C-suite should focus on. Surprisingly, the hype around large language models (LLMs) was not a primary focus in most conference tracks; instead, the discussion focused on implementing the right AI solutions for specific use cases. The market is becoming more nuanced, with discussions around different types of AI taking center stage. Here are my key takeaways from the event:
2024 is the year of AI execution
2023 was about exploration; now it’s time to get serious about AI. Looking ahead, 2024 is poised to be the year of AI execution and multimodal advancements. As organizations move beyond the exploration phase, they will seek partners to help them navigate the implementation challenges. Public failures are likely to occur, impacting the pace of AI adoption. To mitigate risks and build trust, transparency will be paramount. And while execution is the focus, understanding and mitigating challenges before they occur is crucial.
Data leaders should strive for composite AI
Integrating multiple AI technologies, techniques, and models should be the focus. No single AI solution fits all needs; combining AI into a composite AI system can handle a broader range of tasks and solve problems more efficiently than single AI systems.
Data Leaders are challenged
Existing in the tech bubble can lead one to believe that every business leader is as sophisticated and educated about AI as we are – that is not true. One of the key observations from the summit was the overwhelming presence of attendees from non-tech sectors who were in the early stages of AI implementation. This highlights the stark contrast between the conversations in the tech industry and those in other sectors. At Arria, we bridge this gap and guide organizations embarking on their AI journey.
CDAOs will become indispensable
Chief Data and Analytics Officers (CDAOs) will be critical in driving AI initiatives within their organizations. They must position themselves as strategic partners, align AI investments with business objectives, and demonstrate the tangible value of AI-driven insights. CDAOs who can effectively communicate AI’s impact on decision-making and operational efficiency will become indispensable to their organizations.
Governance will be rebranded as a strategic business
Governance, often perceived as a compliance burden, will undergo a rebranding as a strategic business enabler. Effective governance frameworks will ensure AI’s responsible and ethical use and drive innovation and competitive advantage. Organizations that prioritize governance as a core component of their AI strategy will be better positioned to navigate the complexities of AI deployment. Governance emerged as a critical topic at the summit, overshadowing even the buzz around LLMs. As AI becomes more pervasive, establishing robust governance frameworks is crucial to ensure responsible and ethical deployment. We must prioritize developing and communicating our governance strategies to instill confidence in our clients.
Governance will continue to be key to AI value
Governance will remain a critical factor in realizing the full value of AI investments. Organizations must establish robust governance frameworks encompassing data quality, model transparency, ethical considerations, and accountability. By ensuring the responsible and transparent use of AI, organizations can build trust with stakeholders, mitigate risks, and maximize the long-term value of their AI initiatives.
Natural language technologies are the new composers of AI
The release of ChatGPT and the rise of LLMs have brought attention to natural language generation (NLG), the technology sector Arria has been leading for nearly twenty years. The rise of natural language processing (NLP) will revolutionize how we interact with AI systems. Natural language interfaces will enable users to express their needs and objectives in a more intuitive and conversational manner. This shift will democratize access to AI capabilities, empowering non-technical users to leverage AI for decision-making and problem-solving.
Natural language will free data access and use
The proliferation of natural language interfaces will transform data access and utilization. Complex query languages or rigid data structures will no longer constrain users. Instead, they can interact with data using natural language, extracting insights and making data-driven decisions easier. This democratization of data access will empower a broader range of users and accelerate innovation.
Cost is the most significant threat to the success of AI initiatives
More than half of organizations are abandoning their AI efforts due to missteps in estimating and calculating costs related to tokenization, licensing, compute power, and AI-ready data. To avoid unforeseen costs and missteps, you must partner with a proven AI technology company to guide your AI journey.
Intellectual property loss and copyright infringement are risks
As generative AI models become more sophisticated, concerns about these risks will intensify. Organizations must implement robust measures to protect their proprietary data and ensure compliance with relevant regulations. Developing clear policies and guidelines for generative AI will be essential to mitigate these risks.
Humans in the loop are critical
People will prove key to getting value from AI. While AI technologies are powerful, the human element will ultimately determine the success of AI implementations. Organizations must invest in upskilling their workforce, fostering a culture of continuous learning, and encouraging collaboration between domain experts and AI specialists. Organizations can unlock the full potential of these technologies by empowering employees to leverage AI effectively.
GenAI is both the problem and the solution for cost escalation
While offering immense potential, generative AI models can contribute to cost escalation if not managed effectively. The computational resources required to train and deploy these models can be substantial. However, generative AI can also be part of the solution by automating tasks, optimizing processes, and reducing manual efforts. Organizations must carefully assess the cost implications of generative AI and implement strategies to maximize its value while controlling expenses.
Expect new user experiences beyond dashboards
As AI becomes more pervasive, user experiences will evolve beyond traditional dashboards. Immersive visualizations, conversational interfaces, and augmented reality will redefine how users engage with data and insights. These new user experiences will enable more intuitive and contextual interactions, enhancing the overall value derived from AI systems.
As we navigate the year of AI execution and multimodal advancements, organizations seeking to harness the power of AI face clear challenges. By empowering CDAOs, balancing ambition with risk, leveraging natural language, and prioritizing governance, organizations can position themselves for success in the ever-evolving AI landscape. Partnering with companies with experience, knowledge, and tested solutions to mitigate risks is critical.
Arria has been leading the natural language space for nearly two decades. Speak to one of our AI experts to help you on your AI journey.
