AI Integration: Challenges and Opportunities for Enterprises
The year 2025 is forecasted to be pivotal for artificial intelligence (AI), as it promises to deliver specific gains for enterprises, according to industry analysts. But a recent report by AI development firm Vellum shows that only a quarter of organizations have successfully integrated AI into production, and of those, merely a handful have noticed substantial benefits.
As these findings suggest, a substantial number of businesses remain in the early stages of identifying effective AI applications. Akash Sharma, CEO of Vellum, commented on the current state of AI adoption, emphasizing it remains "early days" for AI despite the ongoing buzz and rapidly evolving tools and models. According to him, many enterprises are still in a "pre-build holding pattern," searching for valuable AI use cases.
Enterprises Must Identify Specific Use Cases to See Success
Vellum conducted surveys with over 1,250 AI developers, investigating the real-world deployment of AI within companies. It found that 53% of these companies are in varied phases of their AI journey, such as creating and assessing strategies and proofs of concept. Others are engaged in beta testing or in early discussions with users.
The most common applications include document parsing, analysis tools, and customer service chatbots. Some companies are also exploring analytics with natural language, content generation, and automation tools. Developers cite competitive edge (31.6%), cost reductions (27.1%), and increased user acceptance (12.6%) as significant benefits. However, 24.2% still experience minimal impact from their AI ventures.
Sharma underscored the need for companies to focus on identifying valuable AI use cases to drive real returns, stating that once enterprises find and implement these cases effectively, they often see momentum and investment grow.
OpenAI Still at the Top, But a Mixture of Models Will Be the Future
OpenAI continues to lead in model utilization, with its offerings like GPT-4 and GPT-4-mini, although Sharma notes a growing availability of other options in 2024, including platforms from Azure and AWS. Open-source models are also gaining prominence, with companies such as Llama and Groq making advancements.
Sharma predicts that businesses will increasingly opt for a combination of models, selecting the best fit for each task. This approach allows developers to leverage optimal performance in terms of quality and cost-efficiency without relying solely on one provider.
Everyone’s Getting Involved (Not Just Engineering)
The scope of AI's integration has expanded beyond the IT departments, involving leadership, product teams, and design sectors more extensively. This broader engagement is driven by AI's user-friendly nature, which enables cross-functional development and collaboration.
2025 Will Be the 'Year of AI Tooling' to Overcome Key Challenges
Despite advancements, businesses still face hurdles including AI model reliability, data security, and internal buy-in. Moreover, there remains a notable gap in technical expertise needed to connect AI tools effectively within enterprises.
Sharma highlights the importance of leveraging appropriate tooling to guide AI development, which can help bridge this expertise gap and address many of these challenges.
Evaluations and Ongoing Monitoring Are Critical
Sharma emphasizes the necessity of rigorous evaluations and monitoring to mitigate issues such as AI hallucinations. While some developers employ automated testing, manual evaluations are still predominant, which can be time-consuming and less comprehensive.
In conclusion, Sharma points out the importance of treating AI as one of the many tools available to businesses, rather than viewing it as a catch-all solution.