This article has been written by Maleena pursuing a Training program on Using AI for Business Growth course from Skill Arbitrage.

This article has been edited and published by Shashwat Kaushik.

Introduction

AI is a powerful tool in the present era that has proven significant results if used wisely in any field. Many businesses are using AI to bring good output and development into the business. The decision support system, which was made using AI tools in activities like operation, management, and planning, proved to be more profitable and gave better results than without AI’s support system.

Now let us understand how an artificial intelligence-driven decision support system is doing its job to get outstanding results:

Data analysis

• Forecasting customer behaviours and analysing their demand is important for any business to predict market trends and customer choices so that any business can optimise its stock levels and meet the customer’s demands by supplying them with what they prefer and AI tools and strategies are doing this task in no time, making it easier for businesses and bringing growth.
• Demand and supply patterns can be improved through AI tools to identify the unrevealed patterns of customer segments, trends, and inter-related factors.
• Market analysis and studies of demand and supply, that is, cross-selling strategies and product supply, can be identified and made easier using AI’s Decision Support System.

Customers data

• Customer feedback and satisfaction are crucial for any business to prosper, and AI is doing this very effectively through feedback forms, surveys, and reviews. After getting this vital information, a business can work on customer’s needs, resulting in gaining customer satisfaction and loyalty.
• Creating and designing the product according to the market trends makes it easier for the business production process to manufacture and supply the product without any mistake or delay, meeting the demand on time and saving human time and effort, which leads to cost control and more profits.
• AI features such as voice recognition, predictive analytics, and recommendation engines not only make the products more user-friendly but also add significant value, setting the product apart from the crowd and making the user more indulgent, resulting in customer satisfaction.

Market and sales

• Improving conversion rates using AI tools and Decision Support System, extracting information on customer interaction, behaviour, demographics, and history, and helping the sales team to improve and focus on sales leads. Through this process, the sales team will recognise priority leads, customise the desire, and allocate the resources, which results in high sales and less time spent, which again gets profits for the business.
• AI focuses on CLTV (customer lifetime value), which will be beneficial for any business to prioritise high-value customers and market strategies through personalised loyalty programs and target campaigns that lead to customer retention and satisfaction. This will again lead to an increase in growth and revenue for the business.
• AI not only helps in sales leads and conversion but also predicts market trends and their performance and helps businesses manage and control inventory levels.

 Customer experience

• AI provides the best customer experience through automated recommendations and offers after identifying customer’s behaviours.
• It takes feedback from customers and promotes improvement, best services, and customer interactions.
• AI chatbots and virtual assistance play a vital role in offering 24/7 customer service and satisfying customers by solving their queries effectively. The continuous availability and real-time support not only enhance customer satisfaction but also reduce costs to the business.

Operational efficiency

• By analysing a varied amount of data related to the supply chain, such as logistics, inventory management, procurement processes, supply, demand, and transport routes, AI identifies errors and suggests improvements; this leads to smooth operations and drives better business performance, which leads to customer satisfaction and business growth.
• By using Machine Learning Algorithms and Predictive Analysis, AI can detect fraudulent activities and unusual patterns and flag suspicious ones, enhancing security by learning data that can prevent monetary losses and minimise reputational loss, which promotes trust among customers and partners.
• As AI is effectively helping businesses in planning, managing operations, reducing manpower, cost of production, inventory, and supply measures, it will bring prosperity and growth into the business, and this will again support the business sustainability process.
• AI helps do automated repetitive tasks such as data entry, customer enquiries, and scheduling in a more efficient way that leads to human power saving and cost control, which again leads to minimising errors and enhancing overall productivity.

AI strategies

AI identifies and works on the SWOT analyses of the business, i.e.,

• Strength: the existing asset technologies of business.
• Weaknesses: the inefficiencies and lacking areas.
• Opportunities: market trends, advancements, technologies, and customer needs.
• Treats: identified external threats, cyber security risks, and uncertainties.

 To take out maximum profits from minimum investments.

• AI takes the initiative to identify the KPIs and align them with the business’s overall growth, like identifying the core objective or principle of business and working for its growth; it also identifies related metrics that serve as KPIs of business, such as customer satisfaction, operational efficiency, revenue growth, and product quality.
• Set targets for each KPI for improvement, monitor its growth, conduct periodic reviews, and align with stakeholders like the project manager, executives, and team involved in implementing AI.
• AI helps identify the pain points of business and works on them, like organising stakeholder meetings to gather information about the different challenges they face and uncover the inefficiencies. Analyse operational data like inventory, process cycle time, error rates, customer complaint frequencies, etc.

Map out business functions, delays, redundancies, predictive analytics, or decision support and highlight opportunities. AI compares industry benchmarks with an organisation’s performance to help the business close the gap.

AI use cases

• Once business goals are set, AI prioritises and aligns them with projects based on their potential impact and feasibility.
• Conducts assessments to know the data, available resources, and expertise needed.
• AI focuses on ROI and strategies for overall business growth.

Roadmap

• AI sets a clear roadmap to achieve the business goal using use cases like it sees the objective will be completed in a set timeline.
• It sees the work will be completed with allocated resources, like a specified budget and personnel.
• It tracks the dependencies between projects and milestones.
• Assembling a team of experts in different fields like data scientists, domain experts, engineers, etc.
• Defining roles and responsibilities and communication channels for AI initiatives for smooth execution.

Challenges while implementation

Even though AI can be successful for business, some challenges stop AI from working smoothly, like

• Lack of data or low information for AI to perform well
• Lack of AI-skilled, trained professionals who can develop, implement, and maintain the AI systems
• Lack of system to deal with biased decisions, transparency, and fairness.

To overcome such challenges AI has some solutions

• Robust data collection and management systems that ensure collecting data from partners and also organising systematically.
• Hiring AI-trained professionals up skilling the existing professionals and also partnering for internships with software companies.
• Setting up AI committees for transparency and fairness concerns by setting up regular audits.

Tracking ROI

Measures of tracking KPIs that align with business growth are the next step. To get a clear image of success, the business has to keep a record of financial metrics like revenue and cost. Operational metrics like efficiency, productivity, and cycle time. Customer-centric metrics like customer satisfaction, retention, and lifetime value. And AI’s metrics like positive/negative rates, model accuracy, and predictive accuracy.

AI’s performance

Monitoring AI’s working and growth using AI is very important, as after seeing its performance changes can be made if needed for the business’s betterment.

• Data should be checked for accuracy, preciseness, and relevancy, as the data says AI works on that.
• AI models should be checked regularly on all metrics.
• Data that support bias and transparency should be assessed for betterment.
• A/B testing should be done to improve AI’s performance for the growth and progress of business.

  Calculating ROI

• AI-Driven Support System aims to reduce the cost of investment and increase profits.   Business should be assessed to see the progress in terms of revenue, costs, and risks.
• Expenses incurred on the AI model for planning, maintaining, developing, and implementing should be analysed.
• Net profit should be assessed using the ROI formula = net profit/total investment * 100 to check the returns a business gets after using the AI system.

Not only net profit but also customer reviews and satisfaction should also be checked, as customers play a vital role in any business’s success.

Declaring results

Results should be laid down correctly in front of stakeholders and investors to gain valued support from them in the form of visualisations, success stories, and the overall impact of AI’s performance in business.

Conclusion

Hence, the AI-driven support system is a tool that can reap benefits and welcome drastic changes in any business if follows clear core principles and strategies, lays down a clear roadmap, prepares for the challenges faced, and overcomes them with the help of AI for the growth and development of the business. The future of AI-driven support system business can be rewarding and lead to success in no time. Business leaders who adapt to change and encourage new ideas will be set to achieve significant success in the future.

References

• AI for Business Leaders: Driving Innovation and Growth (capitalnumbers.com)
• Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications – PMC (nih.gov)
• What Are AI-Driven Decision Support Systems? | TEDAI San Francisco
• AI-Driven Decision Support Systems | by SingularityNET Ambassadors | Medium