How To Use Generative AI to Scale Your Enterprise Business
Generative artificial intelligence (AI)—AI that creates content—has taken the world by storm, permeating every corner of our digital existence. I am a business intelligence professional and most of the companies I work with are eager to understand how generative AI can unlock new opportunities for innovation and growth.
Even the plumber who came to my house the other day for a service call was interested in discussing ChatGPT and AI. I wouldn’t have thought that likely five years ago.
We are at an inflection point in humanity where the legal, moral, and ethical implications of these changes are profound and new norms are becoming established. It is both exciting and challenging to keep up with the expanding applications and possibilities that generative AI offers.
I enrolled last year in a no-code data science course at MIT for machine learning and artificial intelligence to ensure I fully understood how this technology can build client-specific solutions. Throughout my coursework, I learned about the different types of machine learning, AI’s natural language processing (NLP) and deep learning techniques from a no-code approach, leveraging tools like RapidMiner to build machine learning pipelines.
I’ll take part in an Upwork webinar this summer to share my knowledge in this space. (We’ll soon include information on how to register for that, so stay tuned.) For now, let’s chat about what we know about generative AI, how others are using it, and some opportunities to consider for your own company.
What we know about generative AI
Generative AI is a form of artificial intelligence that trains on a plethora of data to generate fresh and creative new content across various formats, including text, images, and code. Great examples of generative AI are text-to-image tools like:
Or, text-to-text tools like:
ChatGPT is the text-based chatbot created by OpenAI that made a splash in the large language model world, showing how realistic the outputs can be within the context of human language and how advanced this technology has truly taken us.
As businesses explore the potential of generative AI, it is important to acknowledge the associated concerns and challenges. While generative AI offers numerous benefits, there is a need to address the potential risks and ethical considerations, which are many.
Misuse or manipulation of AI NLP-powered systems could lead to the spread of disinformation or biased content. Ongoing research, responsible development practices, and robust ethical frameworks are essential to ensure the responsible and beneficial use of NLP in generative AI technologies.
Near-term and long-term uses for generative AI
In the near-term, the application of generative AI is set to bring about significant transformations. Its potential impact is especially notable with content creation. With the help of generative AI, creators in design, marketing, and entertainment will be able to streamline processes by automating the production of:
While generative AI can automate many aspects of content creation, it cannot replace human intuition, creativity, and empathy, which are crucial for producing meaningful and emotionally resonant content. As such, businesses and organizations will need to strike a balance between using generative AI as a tool to enhance their creative processes and leveraging the unique strengths of human creators to bring a human touch to their content.
Generative AI holds the promise of augmenting human capabilities, enabling us to push the boundaries of our creativity and innovation.
It also has the potential to disrupt not only jobs, but the mental health of many as we navigate this new era of time and determine what our role in society will be in order to peacefully coexist with machinery that may very well be more intelligent than the average human.
Responsible development and ethical considerations will play a crucial role in harnessing the full potential of generative AI for the betterment of society.
How my company is already using generative AI
My company Omni Business Intelligence Solutions is already leveraging generative AI in ways to help support the scalability and growth of our business.
We use ChatGPT in these 10 areas.
1. Content creation and thought leadership
ChatGPT has helped us generate industry-specific articles, blog posts, whitepapers, and social media content to establish thought leadership and attract high-quality leads and new clients.
2. Business development and proposal optimization
ChatGPT assists in crafting personalized proposals by refining language based on the client's environment and business services, and optimizing content structure and placement within the proposal.
3. Legal contract review and customization
We’ve used ChatGPT to enhance, review, and compare legal documents, adjusting language tailored to each client's business within statements of work and master service agreements.
4. FAQ internal knowledge base
We created an in-house training guide tool using company-specific prompts and hyperparameters to onboard new consultants and team members.
5. Client preparation training guides
We’ve crafted comprehensive training guides that can be duplicated and customized for client teams, providing step-by-step instructions for new implementations or tools built within their environment.
6. Data analysis and decision-making support
We’ve used ChatGPT to validate key insights, interpret complex data patterns and trends, and provide concise summaries using ChatGPT to support data-driven decision-making.
7. Streamlined project management
We generate meeting notes with ChatGPT, with assigned action items for distributed team members at OBIS and for clients, improving collaboration and project tracking.
8. Comprehensive market research
We use ChatGPT to conduct in-depth market research on services and products relevant to client industries, empowering them to make informed investment decisions.
9. Innovative dashboard design
We utilize ChatGPT's creativity to innovate dashboard design and visualization styles to differentiate OBIS in the business intelligence consulting space. (I’ve coined a phrase for this called poetry business intelligence or PoetryBI.)
10. Data transformation support
ChatGPT helps us quickly write complex queries or formulas in tools like PowerBI, Tableau or within structured query language (SQL) data warehouses, facilitating cleaner and more efficient data transformation for existing clients and increasing ROI on contracts.
How other companies are interacting with generative AI
Top companies are interacting with generative AI technology in sophisticated ways. The following real-life examples demonstrate how different companies have implemented, leveraged, and responded to the power of generative AI within their business model to enhance business operations.
Building or acquiring Generative AI capabilities: OpenAI and Microsoft
OpenAI, the organization behind ChatGPT, has developed AI large language model (LLM) capabilities and offers them as a service to businesses. By partnering with OpenAI, companies can access and leverage advanced generative AI models to enhance their customer support, content creation, and data analysis processes.
Microsoft has invested in AI capabilities by creating Microsoft 365 Copilot. Microsoft 365 Copilot is an innovative productivity tool that harnesses the power of LLMs and integrates with the Microsoft Graph, which includes data from various Microsoft 365 applications such as calendars, emails, chats, documents, and meetings. Copilot aims to transform the way we work by leveraging LLMs to turn our words into a powerful productivity tool.
Establishing a robust data infrastructure: Amazon and Facebook
Amazon has established a robust data infrastructure to support generative AI applications. Through its e-commerce platform, Amazon collects vast amounts of customer data, including purchase history and browsing behavior, which fuels AI-driven product recommendations and shopping experiences.
Facebook maintains a comprehensive data infrastructure to enable generative AI applications. By collecting and analyzing user data, such as interests, demographics, and social connections, Facebook's algorithms generate personalized news feeds, targeted advertisements, and content recommendations.
Ensuring ethical and responsible deployment: IBM and Microsoft
IBM emphasizes ethical AI deployment through its AI Fairness 360 toolkit. This toolkit helps organizations detect and mitigate biases in AI models, ensuring fairness and avoiding discriminatory outcomes in areas such as hiring, lending, and criminal justice.
Microsoft has implemented responsible AI deployment practices focusing on ethical considerations, including privacy, transparency, and accountability, to ensure that AI technologies are developed and used responsibly across various applications.
Best entry points for you to apply generative AI to your business
We recommend the following five-step approach for companies wishing to leverage generative AI for business.
1. Identify the right use cases for generative AI
Start by identifying specific areas within your enterprise where generative AI can make a significant impact. This could include content generation, customer support, product design, or data analysis. Consider the challenges you want to address and the potential value that generative AI can bring.
2. Build or acquire AI capabilities
Next, you need to build or acquire the necessary AI capabilities to implement generative AI. This can involve developing in-house expertise or partnering with AI solution providers. Evaluate the available options and choose the approach that aligns with your business goals and resources.
3. Establish a robust data infrastructure
Generative AI relies on high-quality data for training and generating meaningful outputs. Ensure that you have a robust data infrastructure in place to collect, store, and process the relevant data. This may involve data integration, data cleansing, and data governance practices to ensure the accuracy and reliability of your AI models.
4. Ensure ethical and responsible AI deployment
As you leverage generative AI, it is crucial to prioritize ethical and responsible AI deployment. Establish clear guidelines and governance frameworks to address potential biases, privacy concerns, and ethical implications. Regularly assess and mitigate risks associated with AI deployment to ensure fairness, transparency, and accountability.
5. Measure and monitor AI-driven outcomes
To assess the effectiveness of your generative AI implementation, establish measurable metrics and key performance indicators (KPIs) aligned with your business objectives. Continuously monitor and evaluate the outcomes generated by the AI system to measure its impact, identify areas for improvement, and optimize your AI strategies accordingly.
Harness generative AI to unlock unprecedented business opportunities
Generative AI holds immense significance in today's dynamic business environment, serving as a catalyst across various industries. It offers transformative solutions that drive growth, enhance scalability, optimize operational processes, and elevate customer experiences to new heights.
Consider harnessing the power of AI to unlock unprecedented advancement and sustainable success in a highly competitive business landscape. To find out more about OBIS and what generative AI can unlock for you, feel free to reach out and send a message to me here to learn more.
Author: Jacqueline Ann DeStefano-Tangorra at OBIS Editor: Jean Weiss at Upwork