By Ben Xiang, SVP, Product & Engineering, Veritone

Artificial Intelligence (AI), particularly Large Language Models (LLMs), has emerged as a transformative force in business technology. However, the true value of these advanced AI tools lies in their strategic application to address specific business needs. The first–and critically important–step for businesses is to effectively evaluate their needs and align them with appropriate AI solutions, maximizing the impact of AI integration. The place to begin is by examining business operations through a thorough evaluation of your current challenges and opportunities. This process involves assessing areas where efficiency, accuracy, or innovation could be enhanced.

Assessing Current Challenges and Opportunities

Start by conducting a comprehensive analysis of your business processes to identify bottlenecks or inefficiencies. Are there repetitive language tasks that consume valuable human resources? Are there obvious “low-hanging fruit” opportunities for innovation in customer engagement or product development that require extensive language processing?

For instance, consider a customer service department inundated with routine queries. This scenario often leads to long wait times and overworked staff. Identifying such challenges can highlight the potential for LLMs to automate responses, thus improving efficiency and customer satisfaction. LLMs excel in automating routine tasks and enhancing more complex ones, making customer support a prime area where AI can manage routine inquiries, allowing human agents to focus on more intricate issues. Similarly, in content creation, LLMs can produce high-quality content rapidly, freeing up time for more strategic human activities. For example, an e-commerce company might struggle with creating unique product descriptions for thousands of items. An LLM can generate these descriptions automatically, ensuring consistency and saving significant time and effort.

Evaluating Data Availability

The success of LLM implementation hinges on access to substantial and relevant data. Businesses must assess whether they generate enough data to feed and train the LLM effectively. Data such as customer interactions, product descriptions, or research reports are invaluable.

Consider a healthcare provider with vast amounts of patient data. By leveraging this data, an LLM can assist in diagnosing conditions or providing personalized patient care recommendations, thus enhancing service quality and operational efficiency.

Considering Scalability and Impact

When choosing use cases, focus on areas where LLMs can significantly improve outcomes or scale operations. For instance, LLMs can process vast amounts of text data in analytics, offering deeper insights and enhancing decision-making.

A financial services firm, for instance, might use LLMs to analyze market trends and generate reports. This capability not only speeds up the process but also provides more comprehensive insights, aiding better investment decisions.

Common Use Cases of LLMs Across Industries

LLMs are versatile and can be applied in numerous sectors. Here are some impactful use cases demonstrating their diverse capabilities:

Document Summarization

In academic and corporate research settings, LLMs can process extensive texts to extract key information and themes. This significantly reduces the time required to digest large volumes of information, enhancing productivity and decision-making. For example, a law firm could use LLMs to summarize lengthy legal documents, making it easier for lawyers to review key points quickly and efficiently.

Creative Writing Assistance

Authors can leverage LLMs to generate ideas, suggest narrative structures, and even draft content. This helps overcome writer’s block and enhances creativity, allowing writers to produce more refined and imaginative work.

Email and Communication Management

LLMs streamline email sorting, drafting, and scheduling, preserving context and personalizing communication. This boosts productivity by managing routine communications efficiently, freeing up time for more critical tasks.

Personalized Content Recommendation

LLMs analyze user preferences to suggest relevant content, enhancing user engagement on streaming services and online platforms through tailored content suggestions.

Technical Support Automation

LLMs generate technical support guides and troubleshooting tips, enhancing customer support in technology sectors by providing instant and accurate technical assistance.

Copywriting and Advertising

LLMs craft creative marketing copy and promotional material, which are crucial for marketing agencies and businesses and help create compelling and targeted advertising content.

Scripting and Code Generation

LLMs assist developers by generating code scripts, aiding in debugging, streamlining software development processes, and reducing errors.

Resume Screening and HR Automation

LLMs automate the screening of resumes and job applications, making the hiring process more efficient and fair by integrating with applicant tracking systems and utilizing bias-free evaluation algorithms.

Essential Features of LLM Applications

Each use case requires specific LLM features to be effective. Here are key features to consider:

• Conversational Response: Essential for chatbots and virtual assistants, enabling natural, fluid dialogue with users.
• Coding and Math Capabilities: Crucial for code generation and mathematical problem-solving in technical applications.
• Reasoning and Comprehension: Vital for logical analysis, problem-solving, and understanding complex texts.
• Word Knowledge and Fast Response: Important for tasks requiring factual accuracy and real-time interactions.
• Grounded Knowledge and Fine-Tuning: Ensures accuracy and relevance, particularly in professional and educational settings.
• Extended Context and Content Moderation: Maintains coherence over long interactions and ensures safe, reliable usage.

By strategically aligning your business needs with the right LLM applications, you can harness the power of AI to transform operations, enhance efficiency, and drive innovation. The key lies in a thoughtful evaluation of your challenges and opportunities, coupled with a deep understanding of the capabilities of LLMs, ensuring a marriage of business needs with the right AI solutions.

About Ben Xiang

Ben Xiang is SVP of Corporate Development & Strategy and General Manager of aiWARETM for Veritone, Inc. Ben is responsible for overseeing Veritone’s AI Solutions group, product development and Veritone’s proprietary AI operating system. In addition, he also leads corporate development and strategy. Prior to Veritone, Ben held multiple roles with Ingram Micro as the global executive for the IoT, AI, and Mixed-Reality business as well as roles in strategy and corporate development. He has extensive experience in global business operations and cross-border M&A.

About Veritone

Veritone (NASDAQ: VERI) designs human-centered AI solutions. Serving customers in the talent acquisition, media, entertainment, and public sector industries, Veritone's software and services empower individuals at the world's largest and most recognizable brands to run more efficiently, accelerate decision-making, and increase profitability. Veritone's leading enterprise AI platform, aiWARETM, orchestrates an ever-growing ecosystem of machine learning models, transforming data sources into actionable intelligence. By blending human expertise with AI technology, Veritone advances human potential to help organizations solve problems and achieve more than ever before, enhancing lives everywhere.