AI in Business Development: Key Areas of Application and Top Use Cases
Many of us interact with Artificial Intelligence (AI) on a daily basis without even realizing its presence. From email spam filters to face IDs used for unlocking our phones and from smart home devices to Amazon feed recommendations, AI has become a household name today.
The examples of AI we encounter every day are seemingly infinite! Now, imagine the myriad ways AI facilitates business development!
“87% of enterprises believe that AI and ML will help them achieve business goals centered around growing revenue, boosting operational efficiency, and improving customer experiences.”
With its capability to automate processes, enhance productivity, forecast trends, and personalize experiences, AI has become an invaluable asset for businesses of all sizes.
Key Areas Where AI Can Contribute to Business Development
1. Business Growth: Data-Driven Decision Making
Machine learning (ML) algorithms running behind AI analytics engines can process and analyze vast amounts of data quickly and accurately. By deploying AI-based analytics tools, you can extract contextualized and valuable insights from your data to make well-informed and timely business decisions.
Benefits of AI-driven business data analysis:
- Understand customer behavior and preferences, market trends, and sales performance
- Optimize business operations and resource allocation, identify new opportunities, refine marketing strategies, and improve your competitive positioning.
- Make proactive business development decisions powered by reliable data.
2. Customer Gratification: Personalized Experiences
By analyzing customer purchase history, behavior patterns, preferences, and interests, you can tailor your offerings to individual needs. In-depth personalization enhances customer satisfaction, boosts loyalty, and drives customer acquisition.
- Intelligent customer service solutions such as AI-powered chatbots and virtual assistants enhance customer experience by providing prompt and personalized support.
- Insights derived through AI can be used to personalize website experiences, optimize conversion rates, and improve customer engagement.
- AI helps deliver personalized customer recommendations and individualized experiences across multiple channels.
3. Marketing Automation: Tailored Content & Targeted Campaigns
AI-powered marketing automation helps streamline your entire marketing efforts. Thanks to data and algorithms, AI-based marketing automation makes sending personalized content to your customers easier.
Here are a few ways marketers can leverage AI to automate their processes:
- Personalization: Analyze customer data, predict consumer behavior, identify patterns and trends, and send personalized messages to your customers.
- Email Automation: Analyze the performance of your emails in real time and use the data to improve your next set of emails.
- Lead Scoring: AI can be used to analyze your data to determine which leads will likely become customers. This saves your time and money on lead scoring and improves the quality of your leads.
- Lead Nurturing: AI can also automate your lead nurturing process by effectively guiding leads through the sales funnel until they are ready to purchase. This will boost your conversion rates.
- Channel Optimization: With Al algorithms, your marketing team can easily identify which channels are the most effective in reaching your target audience. This allows you to allocate sufficient time and funds to channels with the best ROI.
- Customer Service & Communication: Using AI to respond to customers instantly will improve your customer’s experience and satisfaction while saving time and resources. For instance, AI-powered chatbots can answer frequently asked questions, recommend products, and process orders faster than a human service agent.
4. Sales Performance: Driving Conversion & ROI
AI-powered sales tools can help businesses identify the most promising leads, prioritize sales activities, and personalize sales pitches. By analyzing customer behavior and predicting their needs using AI, companies can provide more effective sales support and create compelling sales pitches.
Here’s how AI can transform your sales process:
- Data Enrichment & Analysis: Data enrichment refers to the process of deriving data from third-party sources and pulling it into an organization’s database, typically a CRM. Leveraging AI will allow you to bring all your customer context in one place. For instance, with a single source of customer information (in your CRM), you can easily understand lead sentiments and topics of interest. That way, you can score and prioritize your leads and personalize your selling strategies.
- Conversation Intelligence: AI-powered conversation intelligence tools allow you to analyze sales calls and pull key insights, recognize the context within a conversation, and uncover the why behind sales performance.
- Sales Enablement: Sales enablement, the process of equipping your salespeople with the right tools and resources to close more deals, can be automated and optimized with AI. For instance, AI helps build and manage dynamic content libraries that can surface relevant information when necessary and even automatically pull the data from these libraries into sales pitches and proposals.
- Pipeline Management & Forecasting: AI helps reduce the probability of inaccuracies in your sales team. With an AI-driven forecasting solution, you can analyze existing data and gain insights into deals and overall pipeline, build forecasts to draw valuable insights and make improved decisions.
- Sales Engagement: Sales engagement involves all the buyer-seller interactions within your sales process, right from initial outreach to customer onboarding. There are two ways AI can help you streamline this process. Firstly, AI helps analyze your data and insights to understand customer needs and pain points. Secondly, AI aids in personalizing and automating your customer interactions.
5. Process Automation: Automate Repetitive, Time-Consuming Tasks
AI helps automate your most time-consuming routine operations and free up your workforce for more critical tasks. Transferring large volumes of repetitive work from humans to automated systems increases your productivity, accuracy, and responsiveness while minimizing the error rate.
Here are a few examples of AI in business process automation:
- Inventory Management: AI-integrated inventory management software helps with accurate stock level maintenance, effective order management, improved demand forecasting, and better supplier management.
- Data Entry & Update: AI-based data entry involves using software systems that leverage ML, NLP, OCR, computer vision, or other AI techniques for extracting, validating, transforming, or entering data from various sources, such as PDFs, documents, images, audio, or web pages.
- Price Optimization: AI can help you set optimal prices for your products and services by analyzing your customer demographics and spending patterns, historical data, market trends, supply and demand changes, and competitors’ prices.
- Reporting: AI helps automate your report generation process by extracting data from different business systems and relevant documents. It also helps perform necessary data manipulations, assemble reports in designated formats, and send them to relevant stakeholders based on the content.
- Fraud Detection & Prevention: AI-based automation allows your financial professionals to reduce errors in transactions and prevent miscalculations and delayed payments.
6. Innovation: New Business Models Expansion
Artificial Intelligence is basically focused on business expansion and helps unlock new business models that were not possible before.
Here are some of the ways organizations today are making that shift and reaping the benefits of AI in a more practical way.
- Unlock New Opportunities: Predictive analytics solutions leverage AI to identify new revenue streams and opportunities, such as upselling and cross-selling products and services.
- Develop New Offerings: AI-based customer insights are used to develop new products and services that meet the needs of their customers, resulting in increased revenue and growth.
- Efficiency & Productivity Gains: AI-based analytics helps warehouses, shipping and transportation companies, fulfillment centers, and similar businesses with fuel optimization, predictive maintenance, and route optimization.
- Coding & Application Modernization: Companies are using AI for application modernization and enterprise IT operations by employing AI to automate coding, deploying, and scaling. IBM’s Project CodeNet, for example, is a large dataset developed for teaching AI to code.
- Convergence with Other Technologies: Converging AI with other technologies, such as IoT, helps create a new paradigm of business models. For example, real-time data collected by IoT sensors attached to equipment or vehicles can be used to rigorously train AI models, which will ultimately help businesses make fruitful decisions.
Download Our Free Case Study Report Now: How Combining AI with the client’s Litigation Strategy helped reduce the Average Case Settlement Time to 1-2 days at a settlement cost of $15000.
AI Use Cases in Business Development
Here are some significant AI use cases impacting major industries:
Healthcare organizations are using AI to improve the efficiency of all kinds of processes, from back-office tasks to patient care.
- AI computer-assisted documentation: This allows clinicians to efficiently maintain medical records.
- AI virtual nurse assistants: Automate patient question-answering, clinical appointment scheduling, and report-sharing with physicians or surgeons.
- Detect & Minimize Dosage Errors: Monitor and flag errors in how a patient self-administers medications in order to enhance patient health outcomes and reduce healthcare costs and hospitalizations.
2. HR & Talent Management
AI influences almost all of HR operations and service delivery, including recruiting, learning and development, and talent management.
- Recruiting: AI-based profile sourcing from recruitment websites, automated screening of candidates using facial recognition, and AI-based interviews.
- Employee Onboarding: AI-powered bots can accelerate employee onboarding processes by providing quicker access to knowledge, personalized results, real-time assistance, Q&A support, and enhanced collaboration.
- Payroll Processing: Automation of repetitive and error-prone payroll processing tasks such as recording overtime, keeping track of timesheets and leaves, and calculating incentives or commissions.
3. Banking & Financial Services
Custom AI banking solutions help reduce banking costs, mitigate financial risks and frauds, and improve the overall banking experience for customers.
- Reduce Manual Work: Automating routine processes such as KYC update, data extraction, validation, etc., will speed up processing times, reduce error rates, and improve regulatory compliance.
- Transaction Monitoring & Fraud Prevention: In digital banking, AI can be used to monitor user transactions, spot suspicious activities in real-time, and take quick measures to address the risks.
- Financial Planning: AI banking chatbots can interact with customers to assist them with financial planning tasks such as setting financial objectives, budgeting, identifying new investment opportunities, etc.
AI in education focuses on developing new solutions for teaching and learning catering to different situations. The ultimate goal is to facilitate learners with flexible, personalized, and engaging learning experiences.
- Personalized Learning: AI helps educators understand the needs of every learner/ student so they can quickly come up with tailor-made learning plans for each student.
- Course Creation: Several online learning platforms use AI to generate smart content and courses that include immersive visualizations, simulations, bite-sized lessons, and other interactive forms of content.
- AI-Based Tutorials: AI-driven tutorials provide additional support to students in understanding their study materials. With these tutorials, students can learn complex concepts by breaking them down into simple learning modules.
The application of AI in the retail industry translates to better experiences, accurate forecasting, and automated inventory management.
- Demand Forecasting: AI can track and analyze customer data to improve demand forecasting, make pricing decisions, and optimize product placement.
- Inventory Management: AI-based inventory management software can automatically track out-of-stock items, missing inventory, pricing errors, expiring stocks, surplus inventory, etc.
- Returns Management: Intelligent bots can reduce the volume of manual work involved in managing and processing returns by collecting necessary information from customers, guiding them through the return process, sending notifications, and updating inventory databases.
How Fingent Helps Organizations Leverage AI for Business Development
“94% of global business leaders believe AI is critical to success over the next five years.”
Artificial intelligence has a unique and powerful role to play in addressing many of the challenges presented to us today. The question is no longer about adopting AI for basic process automation. It is now about unleashing the potential AI holds to drive new opportunities for our businesses, employees, and society at large.
Fingent offers custom AI software development services to accelerate your business’s growth and profitability. Our AI software development experience spans multiple industry segments, including education, corporate learning systems, litigation, human resources and people management, insurance, retail, real estate, and more.
If you are planning to build custom AI software for your business, want to know more about the scope of AI in business development, or want to upgrade from legacy software to a modern technology platform, feel free to connect with our team.