Unlocking ROI: How Small and Medium Businesses Can Leverage Generative AI like Gemini and CoPilot
The AI Advantage: Assessing the ROI of Gemini and CoPilot for SMBs and Emerging Enterprises
In today's rapidly evolving technological landscape, small and medium businesses (SMBs) are constantly seeking innovative ways to gain a competitive edge. One of the most promising advancements is generative AI, exemplified by platforms like Gemini and CoPilot. These AI systems have the potential to revolutionize how businesses operate, offering solutions that range from customer service automation to creative content generation. However, investing in such cutting-edge technology requires a clear understanding of its potential return on investment (ROI). This blog will explore how SMBs can unlock the full potential of generative AI, demonstrating its practical applications and providing a roadmap for assessing its impact on the bottom line. Whether you're a small business owner or a decision-maker in a medium-sized enterprise, this guide will help you navigate the complexities of integrating AI tools like Gemini and CoPilot into your business strategy, ultimately maximizing your ROI.
Before we delve into the ROI for onboarding these tools in your organization, let’s understand the costs associated when implementing these tools and platforms.
Software and Licensing Fees - These can range from a few dollars per user per month to larger enterprise licensing fees, depending on the AI platform and the plan chosen. For example, CoPilot offers different subscription tiers, and GitHub Copilot typically charges per user. Enterprise-level solutions, like those from OpenAI for business, may come with custom pricing. Enterprise grade platforms like Microsoft CoPilot and Google Gemini charge $20 and $30 USD per user/month, one-year commitment depending upon if you buy Business or Enterprise SKU. Microsoft CoPilot comes at $30.00 per user/month for Business SKU. These SKUs require underlying licenses for Google Workspace and Microsoft 365 Business Basic, Standard or Premium which comes at an additional costs.
Caution: As a small business, if you are using digital workplace platforms other than Google or Microsoft, these tools may not support those platforms without having the underlying licenses in place.
API Access Fees: If the generative AI services are accessed via APIs, there may be charges based on usage (e.g., number of requests or volume of data processed). The use case here are very specific to your homegrown applications, or third party applications that can integrate with Generative AI that consume these platform via API, that can be charged per bulk consumption.
Caution: Familiarize yourself with the pricing structure of the AI service provider. This usually includes costs based on API calls, data volume, or usage time. For some use cases, consider open-source AI models that can be hosted and customized on your own infrastructure, which may reduce API costs.
Implementation and Integration: Costs for consulting services to assist with the integration of AI solutions into existing systems and workflows. This could include custom development, API integration, and tailoring the AI models to specific business needs.
Training: Costs associated with training staff to use the new AI tools effectively. This may include formal training programs, workshops, and online courses. Development of internal documentation, guidelines, and resources to help employees understand and leverage the new AI systems.
Legal and Compliance: Costs for ensuring compliance with data protection regulations and addressing legal concerns related to AI use, such as intellectual property issues. Additional Expenses for conducting audits to ensure that the AI systems adhere to relevant legal and ethical standards. This cloud include implementation of DLP tool, and/or monitoring tool to avoid misuse of your generative AI platform.
Once we have the total cost of ownership in place, the next step is to identity the benefit parameters and associate quantifiable financial benefit to it.
Quantifiable Benefits:
Cost Savings: Reduction in labor costs due to automation, decreased error rates, and improved operational efficiency. This may not be necessarily around reducing labor force, but slowing down the hiring of additional labor force, while increasing your workload inline with your sales revenue. Your existing force may be able to do more with the tool than they are doing today. For E.g. a Sales Manager would be able to create faster quotes, a business analyst may be able to run quick analysis on the problem statement, or a paralegal may be able to processes historic case data, and current case data faster without going through tons of documentation.
Revenue Increase: Potential for increased sales through improved customer experiences or new product offerings. These generative AI tools help you analyze customer interaction in your emails, CRM, ITSM, and other apps that helps you identify opportunities to increase your revenue with the customer.
Productivity Gains: Enhanced productivity through faster processing times and improved decision-making capabilities. An average information workers leverages several resources at their disposal, before delivering their work. A sales manager could be going through customer info internally on their system as well as externally on various portals. Tools like CoPilot or Gemini can help them create a summary of past interaction, behavior patterns, and create more relevant proposals and presentation in a short time. Underwriters can query copilot for previous resolutions on several issues and leverage them on their decision making, instead of repeatedly referring to their next levels. The productivity gains are derived from these information workers doing more within available resources.
Qualitative Benefits
Improved Customer Satisfaction: Enhanced customer interactions and faster response times. Providing faster response to customer using both self services, as well as assisted support can result into higher customer satisfaction. A survey released recently shows higher CSAT when used generative AI supported customer service, as compared to basic knowledge base driven. This was visible in the various NPS Survey where more people chose to recommend their products and services when they had faster access to information or support they wanted.
Brand Reputation: Strengthening the brand as an innovator and leader in technology adoption. This is directly linked to Improved Customer Satisfaction, as more and more customer would act as brand ambassador through various channels. From reviewing their product and services on mobile app stores to providing testimonial, all this is an indirect result of improved customer service.
Employee Satisfaction: Reduction of mundane tasks, allowing employees to focus on more engaging and strategic activities. Nothing demotivates an employee more than mundane & repetitive tasks, and lack of budget to custom automate them. Generative AI has been considerably useful when automating these tasks via CoPilot or Gemini. E.g. when a sales person has to provide competition analysis of various products and services they offer, a simple prompt to CoPilot or Gemini shows them the equivalent competition products, and their USPs. A procurement leader creates various prompts about spend comparison of the companies of their level before negotiating with their vendors and partners.
To determine the return on investment (ROI) of implementing generative AI tools like Gemini and CoPilot, it's crucial to quantify both the tangible and intangible benefits. Tangible benefits, such as time savings and increased revenue, can be easily converted into dollar values. However, intangible benefits, such as improved customer satisfaction, require a more indirect approach, like estimating their impact on customer retention or lifetime value.
It's also important to consider the inherent variability and uncertainty in any cost-benefit analysis. Factors like fluctuating costs, unpredictable market conditions, or unexpected events (like a pandemic or war) can significantly influence the outcome. Conducting a sensitivity analysis can help you understand how changes in key assumptions affect the ROI,giving you a clearer picture of the risks involved.
For instance, consider a scenario where employees working remotely have limited access to training resources.Generative AI tools can empower them to create drafts and deliverables independently, bridging the knowledge gap and ensuring productivity even in challenging circumstances.
If you're a small or emerging business looking for an unbiased assessment of the potential ROI of generative AI for your organization, don't hesitate to reach out. I can help you create a tailored business case that aligns with your specific goals and needs.