AI in Business Development

Leveraging AI in business development enables organizations to hone marketing strategies, capture more market share, identify new markets and make smart product development decisions. In this article, we’ll examine AI’s unique value proposition for business development, sharing where AI-driven technologies are having the greatest impact. We’ll highlight specific examples that demonstrate the ways in which data-driven businesses are harnessing AI for innovation and sustainable growth.

When to Use AI-Enabled Approaches to Business Development

For many business development use cases, modern rules-based automation tools are sufficient. The real value of AI lies in its ability to analyze data at scale, and extract insights from complex data sets to increase speed and improve the accuracy of results. It’s also important to note that, although AI has much to offer for business development processes, it’s not a replacement for human judgment, critical thinking or industry experience. For example, Al can score leads and flag existing customers most likely to churn, but AI alone can’t design a customer journey that will attract and retain customers.

Advantages of Using AI for Business Development

Organizations that integrate AI into their business development processes can experience substantial benefits. Intelligent systems help decision-makers plan and implement smart strategies that support sustainable, long-term business growth.

Self-learning

Unlike traditional rules-based systems, AI systems don’t require reprogramming to improve over time. Using progressive learning algorithms, AI models can automatically adapt as they are exposed to new data. Unsupervised learning models can recognize complex patterns and relationships within data independently, automatically improving their performance over time as they are exposed to new data.

Intelligent automation 

AI can be used to identify tasks and processes ideal for automation and assist with automating workflows. Applications of AI for business development automation include managing accounts, identifying upsell and cross-sell opportunities, and improving retention rates.

Scalability 

AI is highly scalable, allowing organizations to grow over time. Businesses can easily add more data, users and applications without significant re-engineering costs. Pretrained models provide additional flexibility and can be quickly fine-tuned for new AI business development use cases.

Advanced data analytics capabilities

Certain types of AI, such as machine learning and deep learning, can process complex, multidimensional data that traditional data analytics methods cannot. Natural language processing (NLP) is capable of analyzing unstructured data, including text, images, and video and audio data, providing a more complete picture of the issue at hand. This same technology enables conversational interfaces for analyzing data, making it possible for users to query data using natural language. 

Applications for AI in Business Development

There are numerous ways in which organizations can apply AI-enabled technologies to enhance their existing business development efforts. Let’s take a look at a few examples.

Market research

Market research is essential to business development, providing the data organizations need to understand their target market, identify new opportunities, and make strategic decisions regarding product development, pricing and distribution channels. AI can significantly accelerate market research practices. One example is the use of NLP tools that automate the analysis of large amounts of unstructured text data such as customer survey responses, social media posts, online reviews, forum content and more. Using these systems, businesses can efficiently uncover actionable insights about their customers, including brand perception, preferences and pricing sensitivity, as well as broader market trends and industry growth opportunities.

Strategic planning

AI can be invaluable in supporting strategic planning. Predictive intelligence aggregates and analyzes historical and real-time data to detect emerging trends and changes in market dynamics, making it possible to anticipate probable scenarios such as changes in consumer demand for certain products or services. These tools can also  provide a menu of potential options for capitalizing on them, helping human decision-makers establish short- and long-term goals, and create action plans with timelines, budgets and responsibilities.

Growth and diversification 

AI tools can help businesses identify underserved market segments ripe for growth. Using predictive modeling, AI can generate demand forecasts for products and services in new regions and demographic groups, providing the information needed to evaluate which expansion opportunities represent the greatest potential value. 

Competitive intelligence

One of the primary benefits of using AI in business development applications is its ability to continuously analyze new data. This feature is especially useful for tracking the promotions, new product offerings and new market entries of competitors. AI systems gather data from websites, press releases, social media, product reviews, job listings, marketing materials and other sources, and then flag competitive threats and uncover opportunities that competitors have overlooked.

Customer relationship management (CRM)

AI can help businesses better manage their relationships with customers, increasing customer satisfaction and retention. One application is churn reduction. AI systems can sift through massive amounts of customer data with potential relevance for why some customers become former customers. These sources may include demographic and psychographic data, customer service interactions, transaction histories, pricing changes, frequency of use, and competitive pressures. By analyzing this data as a whole, AI-enabled CRM systems can make complex connections within this data, proactively identifying those customers most likely to churn while time remains to re-engage them. 

Fuel AI-Driven Business Development with Snowflake 

With Snowflake Cortex (in public preview), you can quickly and securely analyze your data and build AI applications via an intelligent, fully managed service that serves industry-leading large language models and vector functions. Snowflake provides appropriate models for each feature, so you don’t have to be a machine learning expert or developer to use them. All you need is your data.

Snowflake supports scalable pipelines, enables data preparation for ML model building and integrates with various development interfaces, enabling you to build from familiar tools while efficiently and securely processing the data in Snowflake. And with Snowpark ML, you can quickly build features, train models and deploy them into production — all using familiar Python syntax and without having to move or copy data outside its governance boundary. Snowpark Model Registry (in public preview) makes it easy to manage and govern your models at scale. Power your AI-powered business development initiatives with Snowflake. 

At the Data Cloud Summit 2024, Snowflake’s app and AI summit, join industry peers and product leaders to learn how Snowflake empowers teams to use AI and ML in everyday analytics, build models and apps in minutes, and execute custom workflows such as fine-tuning with ease.