What Generative AI Means for Business Leaders Right Now

Rating — 5·21 min·January 18, 2024
What Generative AI Means for Business Leaders Right Now
What Generative AI Means for Business Leaders Right Now
What does generative AI mean for businesses? How can you start using this technology? And what changes should you expect in roles and responsibilities across your organization after implementing AI? Read this article to understand generative AI meaning.
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Key takeaways
  • Generative AI is an emerging technology that is changing the way we tackle business tasks. It brings businesses new opportunities to be more creative, efficient, and productive.
  • To stay competitive and adapt to new customer expectations, it’s essential for businesses to implement GenAI in their internal processes, products, and services. As a business leader, you can start by using AI for your routine tasks, promote its implementation across your company, and think about integrating GenAI models into your business ecosystem and the products you sell.
  • When implementing generative AI in your business, it’s important to think about how it will affect the roles and responsibilities in your company. This will help you minimize harm to people as a result of AI adoption and create ethical and legal frameworks to ensure data security and privacy.

 

Every technological revolution leads to job changes. Nowadays, one of the most transformational and impressive technologies the world is experiencing is generative artificial intelligence (GenAI). Since it became available to the masses, we have seen how this technology is changing the way businesses across various industries operate and affecting roles and responsibilities in organizations.

The acceleration of GenAI implementation raises questions, especially among business leaders who want to know What is the meaning of generative AI for our company?

At OpenAI’s first developer conference, Sam Altman, CEO of OpenAI, said:

“We believe that if you give people better tools, they will do amazing things. We know that people want AI that is smarter, more personal, more customizable, and can do more on your behalf. Eventually, you’ll just ask the computer for what you need, and it’ll do all of these tasks for you.”

 

 

This is exactly what is now happening with GenAI. Its implementation means increased productivity, efficiency, and competitiveness. C-level executives find new ways every day to apply generative AI technology to marketing, sales, development, management, and other business processes to improve the workflow, free up time for high-priority tasks, and reduce expenses. At the same time, generative AI brings new risks that force business leaders to slow down, consider various scenarios, and find ways to implement GenAI in their business without harm to employees, privacy, and security.

Nevertheless, it’s clear that ignoring this technology is not an option if you want your business to grow, bring value to clients, and hold a stable position on the market.

So where should you start to make GenAI benefit your business, products, and services?

If you think that implementing generative AI in your business means building and training your own model first, we can assure you that there are much easier and faster ways to take advantage of artificial intelligence capabilities. In this article, we share three ways of implementing GenAI that you can consider as a business leader. You’ll discover how other business leaders leverage this technology and what results they have already achieved so you can find your own starting point for GenAI implementation.

Enhance your own workflow with generative AI

If you want to change the world around you, start by changing yourself. There is no better way to understand the capabilities of GenAI and what benefits it can bring than exploring this technology for yourself.

Where should you start? By getting a basic understanding of the technology.

The questions we frequently ask when facing new technology are simple: What is it? and How can it help me? Answering these questions is a good start to explore GenAI, understand its capabilities, and find your own way to apply it in practice.

Understanding GenAI’s value: generative AI vs traditional AI

traditional ai vs generative ai

What is generative AI, and what is so special about it?

The short answer is that GenAI is special because of its versatility, efficiency, and convenience. These are things that traditional AI models can only partially offer.

Since 2012, it has been possible to apply traditional AI models for many tasks that involve forecasting, classification, decision-making, planning, or natural language processing. However, to use the benefits of these models, companies needed to have a significant amount of training data and invest a lot of time, money, and effort in training their models to perform business-specific tasks. That’s why traditional AI was only accessible for corporations with large budgets and separate R&D teams.

Ten years later, generative AI models made most of these benefits accessible to everyone. GenAI models are pretrained on vast amounts of data and use knowledge from that data to generate something entirely new, showcasing creativity and adaptability beyond predefined instructions. This makes it possible to use GenAI for both non-generative and generative tasks, unlocking many more opportunities for businesses.

You can train a GenAI model with additional labeled data for specific purposes (this process is called fine-tuning) or prompt it with a text in natural language to get more precise results (this process is called prompting). While fine-tuning may seem necessary for making a GenAI model perform well for your business-specific tasks, a recent Medprompt study by Microsoft shows that prompting can be enough to achieve the same results. Relying on prompting can save a lot of time and resources, resulting in a GenAI model performing well and providing you with the desired result while eliminating the need for extensive training.

How can GenAI be helpful in business? Here are a few examples of how you can use this technology and what you can get with it:

  • Automation. Generative AI models can automatically create new content such as text, images, and videos. For example, you can give a trained AI model a prompt of what landing page you want for your website and it will generate a landing page according to your request in a few seconds.
  • Enhanced productivity. Every business has to deal with a variety of repetitive tasks, such as creating reports or filling out spreadsheets. GenAI can deal with these tasks faster, making you more productive.
  • User experience personalization. By finding patterns in data, GenAI models can predict and adapt to user behavior, enhancing the user experience with your product or service. Great examples of this are the Netflix recommendation system and chatbots that can keep up a human-like conversation.
  • Improved decision-making. Reacting quickly to market changes and optimizing your business processes are important skills for maintaining your business growth. AI tools can help you analyze real-time data faster to make reasonable business decisions and build successful strategies.
  • Innovation and creativity. Being creative is what helps us find ways to improve our workflow, attract new clients, grow, and stay competitive. GenAI can help you generate new ideas and maximize your potential.

Use GenAI in your own workflow

You now know generative AI’s meaning and what value it can bring to you. But knowledge won’t bring you any profit unless you put it into practice. Here is how Ankur Agrawal, a leading partner at McKinsey, describes his approach to understanding generative AI:

GenAI and some of these technologies are like swimming: You need to really swim in the water to learn.

 

 

So, it’s time to think about how you can use generative AI at work. You probably have some areas in your work routine you’d like to automate or at least speed up. To find the practical value of AI in your own work, all you need to do is test out available AI solutions.

Is there a new AI tool that can be helpful? Try it out! Do you think it can automate part of your monotonous tasks? Sign up, apply it to your tasks, and evaluate the result. Overall, don’t be afraid to explore everything new and potentially useful. It can take some trial and error, but we’re sure that you’ll find a way to make AI tools work for you.

Here are a few examples of what you can start with to experience GenAI in action:

  • Automate scheduling. Busy schedules are hard to manage, but not with the help of artificial intelligence. AI tools like Motion and Clara can automatically find a free spot in your calendar to schedule a meeting, create invites, reschedule existing meetings, and make sure meetings don’t overlap with other tasks. You can sync Motion with your Google Calendar and Clara on your business emails to have meetings automatically arranged at a time that’s suitable for you and your team or clients.
  • Draft responses to routine emails. Generative AI applications can become a great helper with your emails. For example, Emailtree.ai allows you to communicate quickly with smart replies. It’s basically an AI knowledge base that can process data (your past responses and clients’ feedback), learn from it, and provide high-quality replies relevant to specific emails.
  • Get insightful summaries on various topics faster. Don’t have time to surf tons of resources to get the desired information? Tools like Bard can help you to do it faster. Bard is a conversational AI-powered bot that can provide you with information on a topic, quickly summarize articles from the internet, and give answers to various questions.
  • Automate reporting. You can free yourself from manual report writing by delegating this task to GenAI models, particularly LLM (Large Language Models) like ChatGPT or Claude that can read and understand text, analyze it, identify key insights, and summarize it. All you need to do is provide data that your report will be based on and give precise instructions to the model.

To start working with the tools mentioned above, you don’t need a team of developers. And the good news is it won’t cost you a fortune. The price of a monthly subscription to off-the-shelf GenAI solutions starts at around $30, and some are available for free. These options are accessible and affordable; they give you a wide variety of opportunities for automation, productivity improvement, and ideation.

Thinking of GenAI implementation as a game is a good approach to unlock its potential. This is an emerging technology, so every day, someone discovers new generative AI use cases, finding innovative ways to use it across various industries. Be curious, make it a habit to research the latest web development technologies, and don’t be afraid to experiment — you may find a perfect way to take advantage of GenAI and make it work for your business.

Promote GenAI use among your team

An important step towards implementing GenAI in your business is promoting this technology among your team. Let’s see what steps you and your employees can take to harness GenAI models in business processes.

Rethinking roles and responsibilities in your company

Innovation and risk are two sides of the same coin. While implementing GenAI is a powerful way to accelerate your business processes, it also brings new challenges.

One of the main concerns AI raises among business leaders is how roles and responsibilities will change with its use. While exploring the capabilities of this technology, you also need to determine how responsibilities in your organization will change and what steps you should take to adjust recruiting and training. What can you do for generative AI risk management? Here are a few points to consider:

It’s here not to displace humans; it’s here to augment them; it’s here to power them.

 

 

  • While the capabilities of generative AI systems are vast, it doesn’t mean that they can automate everything human workers do. GenAI is a tool that helps you and your team expand your abilities, work more efficiently, automate monotonous tasks, and focus on what matters most to bring new value with your products and services.
  • Define competencies to look for in people you hire. It’s clear that AI is here to stay, and implementing this technology in your business is a long-term process. It involves changes in responsibilities and job requirements. What skills do you want to see in your future employees? Fluency in technology and solid skills in prompt engineering may be two of the important competencies for an AI-powered company.

  • Encourage your employees to adopt a tech-savvy mindset. You might have noticed that almost every day something new happens around artificial intelligence. The landscape is changing at light speed, and to keep up with the changes and get the most out of the latest technologies, you need to be curious about technology and create a culture of continuous learning in your organization. How can you do this? Start by helping your team understand the meaning of generative AI for their productivity and efficiency. We have some ideas for you in the next section.

Exploring effective ways to use generative AI

Generative AI is capable of helping with numerous tasks. Here is how Jonathan Secler, a product marketing executive at Dell Technologies, explains what generative AI means for businesses:

This [GenAI] is about changing the game from an employee productivity standpoint.

 

 

We totally agree. Everyone can find a way to use generative AI in their work, whether they are a sales manager, designer, SEO specialist, PR manager, or developer. What can you do as a business leader to encourage your team to integrate AI into their workflow? The best way for your team to understand the value of generative AI is by trying it in practice.

What exactly can your team members apply AI for? Let’s see.

how can your team use genai

Create complex documents with ease

Writing reports, bids, contracts, and other business documents is a monotonous task that requires focus and time. But what if you assign it to a generative AI system? With natural language processing (NLP) and machine learning (ML) at the core of GenAI models, they can create human-like text following a certain style or tone of voice.

Wondering how good AI-generated documents can be? Tony Lombardo, CEO of construction and real estate company Lendlease, said in an interview that AI assists Lendlease in creating complex bid documents that can be 200 pages long, and the results are impressive: AI generates documents that are about 80% right. Moreover, you can improve the generated document accuracy by giving a model additional instructions in natural language. The more precise your prompt, the better the output you get.

Create graphics for ads, articles, and blogs

Getting unique images for your business purposes is now easy with machine learning models called generative adversarial networks (GANs). Their work lies in the use of two artificial neural networks: the first generates a specific image according to a user’s prompt, and the second decides how close the generated image is to images and descriptions found on the internet.

How generative AI is changing creative work is truly impressive. A lot of designers, architects, and videographers have already tried this technology in action and seen great results. Your team can do the same. Experiment with tools like Dall-E and Midjourney to generate visuals for social media posts, presentations, articles, and ads in seconds. All you need to know is how to formulate a precise prompt to get the desired output.

Get more ideas in a matter of seconds

We frequently need creativity at work. Marketers, copywriters, PR managers, and other specialists can waste a lot of time coming up with a catchy slogan, an interesting topic for a new article, or an attractive social media post. Brainstorming may sound like fun, but it can take a lot of precious time from your team members. Why not use the power of AI systems to boost your efficiency? Tools like ChatGPT, Notion AI, Claude, and Bard can give you some ideas, help you look at your task or topic from another perspective, and inspire you to do something creative and innovative.

Get deep insights from customer feedback

Customer feedback is essential to improve your products and services. But it can take a lot of time to analyze all feedback, sort through it, and finally get useful insights for your business.

Generative AI can come in handy for this task. It is exactly how Ayzenberg, an advertising agency in the game industry, used Glimpse AI. They got a lot of feedback from members of minority groups on video games and wanted to turn it into meaningful insights into problems players frequently face. As GenAI is able to find patterns in data and understand sentiment and tone of voice, it helped a lot with analyzing and categorizing players’ feedback. As a result, Ayzenberg saved a lot of time and got well-structured information that later was used to improve the gaming experience for members of minority groups.

Plan projects in a data-driven manner

Managing resources and keeping track of project execution can be easier if you delegate some work to AI algorithms. Project managers can find tools like Project Insights and Forecast useful for planning and rough estimation. These AI-powered tools use historical data to predict project costs and timelines, optimize resource management, and more. They won’t replace PMs in your team, but they can make PMs more productive, allowing them to see the bigger picture, quickly analyze previous projects, and use discovered information to optimize project execution.

Write code and reduce development time

Developers can use AI tools to enhance their workflow. For example, GitHub Copilot can help you write code faster by providing suggestions as you’re writing. It works for numerous languages and frameworks, and if you provide a bit of context, it will give even more accurate suggestions.

Many developers have already tried GitHub Copilot and shared their thoughts on how effective AI is and how to use it to get good results. One LinkedIn member who uses Copilot through the GPT-4 dashboard says that he has gotten correct code and detailed explanations from it. However, he also mentions some flaws of generative AI platforms due to their limited knowledge base and potentially outdated information. Nevertheless, GenAI definitely has the potential to assist developers in their work.

Automate conversations with customers

Communication with customers is another process where you can use GenAI, particularly large language models (LLMs). We mentioned earlier that large language models are good at understanding not only the meaning of a text but also its context, style, and negative or positive sentiment. They can use this information to provide more personalized, human-like answers.

At Clockwise Software, we built a system powered by GPT-4 to enhance communication with potential clients. We trained the generative AI model on our previous communications and answers so it can generate responses that are relevant to clients’ questions. It works well and has helped us to send almost three times more responses to potential clients compared to what we could do without AI’s help in the same amount of time.

Automating conversations is a bit harder than brainstorming or creating articles with AI, as you need some technical knowledge to train AI models and integrate them into your business. However, everything starts with enthusiasm and research.

Before implementing GPT-4 in our business, we had been actively following advancements in AI, especially in the realm of LLMs. We went from writing articles like What is GPT 3? to using a GenAI model that benefits our business and our clients. And we continue to keep abreast of the dynamic AI field to find ways to harness its potential.

If you want to integrate generative AI chatbots into your business tool or build a custom AI-powered system that will replace a dozen third-party tools and cover all your unmet needs, we can help you with it. Just contact our team to find out how you can automate your workflow.

While we’ve highlighted a few GenAI use cases, the versatility of GenAI extends far beyond what’s mentioned here. For example, QA engineers can use generative AI tools throughout the software testing lifecycle, while HR managers can use them to scan CVs and find the best candidates for a position.

Describing every possible use case would turn this article into a book. So we suggest you explore other possible ways to apply generative AI technology in your business on your own (tip: you can ask ChatGPT or Claude about GenAI use cases) and encourage your team to do the same.

Integrate GenAI into your software

We’ve already shared some generative AI examples and use cases that don’t require many technical skills or much GenAI knowledge. Let’s say you and your team have found ways to apply generative AI tools in your routine. You are actively using generative AI platforms like ChatGPT, Copilot, and DALL-E to improve your productivity, get new ideas, search for information, and more. At this point, you may understand what processes in your business can be safely and effectively automated with AI and want to integrate GenAI into your existing software or provide AI-based functionality in the products you develop.

Integrating artificial intelligence into your business is a whole new level, requiring something more than basic knowledge of AI and access to off-the-shelf solutions. Let’s take a look at how you can do it.

Integrate GenAI models in your business ecosystem

Let’s take as an example the integration of a chatbot or virtual assistant into your existing custom ERP or CRM system. This can be a great way to improve your business processes and customer experience. How can you do it? Here are a few points to consider:

  • APIs for connecting GenAI tools with your software. An API allows you to use the capabilities of external tools within your software. For example, with OpenAI’s API, users can access models like GPT, train it with their own datasets to perform specific business tasks, and integrate it in software. While OpenAI’s API is commercial (you can check pricing on the OpenAI website), there are comparable open-source tools that are flexible and cheaper. However, many companies find commercial APIs more reliable and easier to use.
  • Technical specialists. To integrate AI with your software, you need specialists with relevant experience. Think about your software development team structure, or consider outsourcing this task to a software development company. You may need a data scientist, software engineer, designer, and data engineer.
  • Data.The quantity and quality of data a model is trained on can affect its output. If you want a model to perform specific tasks, you might need to prepare and use your own business-specific data to tune the model. Or, if you don’t have enough data for fine-tuning a model, you can use the help of experts in prompt engineering to get the most accurate, relevant, or creative outputs from the GenAI model.

In some cases, it may be best to opt for a new custom AI solution instead of enhancing your existing software. This will require more money, time, and other resources, so we recommend consulting with a tech specialist (for example, you can use CTO as a service or reach out to an IT outsourcing company for help), weighing all the benefits and risks, and considering how creating a custom AI solution aligns with your business strategy.

If you find a custom AI-powered solution a reasonable option for your business, you need to know how to approach the software product development process. We will describe it in detail in the next section.

Power your products and services with GenAI models

We’ve figured out how you can improve internal business processes with AI. But what does generative AI mean for the products and services you provide to your customers? GenAI can bring value not only to your internal team but to your clients and users as well.

Consumers are getting used to the effectiveness of AI, which helps them satisfy their needs faster and easier. Adapting your products to new user behavior is key to staying in demand. Implementing GenAI is a necessary step to bring the value users expect.

You can enhance your existing products by integrating AI into them in the same way we explained above. But what about your future products? Although AI models, especially LLMs, are becoming more and more accessible, building AI-powered solutions is still quite expensive. And you want to make sure that your product brings you positive ROI, right?

How should you approach the development of GenAI-powered software?

Similarly to how you would build a startup. Take small steps, moving through the stages of a startup, from ideas and planning to building a minimum viable product (MVP), then improving it in an iterative manner. Let’s take a look at these steps in detail:

  1. Identify what user needs you can cover with GenAI. You need to understand the purpose AI features will have in your software. Conducting project discovery is the best way to determine users’ needs, software goals, and limitations. It’s like creating a roadmap for a startup: choose a direction, then identify key steps, milestones, and goals you want to achieve that will help you move further with a clear product vision.

  2. Plan development. Once you have a product roadmap, you need to turn it into an actionable plan: define and prioritize features, estimate time and resources, etc. Besides all the common aspects of web app development, you also need to think of suitable technical pathways to integrate AI into your product, what specialists you need for it, and what data you need to train a GenAI model.

    You may also want to prove the feasibility of your product through a proof of concept in software development, which can help you identify flaws in your initial plan and avoid them during actual development.

  3. Build a minimum viable product. MVP for startups is a good way to save money, reduce the time to market, and get real users’ feedback to improve your product. When developing GenAI-powered products, we recommend using the same approach and starting by building an MVP. Create minimal functionality, test how it works, launch it for early adopters, and get insightful feedback for further improvement.

  4. Use an iterative approach. Software development companies frequently develop products according to an Agile methodology: the team works on the product in iterations (sprints), implementing a particular set of functionality during each sprint and using insights from past sprints to plan future sprints, effectively address issues, and mitigate risks. We recommend you follow the same approach when developing a custom GenAI solution.

You can develop your AI-powered software in-house if you have a team of technical specialists. However, it can be beneficial to outsource app development. As a SaaS software development company, we are ready to help you through all stages of the SaaS development lifecycle to build a cloud-based product that you can use internally or monetize via the SaaS model.

Final Thoughts

How will generative AI change the world? In our opinion, as AI becomes more and more accessible, it changes customers’ behavior, business leaders’ and employees’ approach to routine tasks at work, and responsibilities in different job roles.

People adopt this technology at high speed for personal use, and companies implement AI in their business ecosystems to get an edge over competitors or at least keep pace with the evolving business landscape and customers’ needs. John Larson, a partner at McKinsey, highlights one of the benefits GenAI brings:

The way we’ve been improving customer operations has been incredibly manual. […] So actually one of the things that we are excited about are the applications with generative AI that are helping reduce that operational gridlock

 

 

GenAI gives business leaders an opportunity to address unmet user needs and remove bottlenecks in business processes, making your business more efficient and successful.

However, GenAI also brings new risks. Business leaders are concerned about data security, the accuracy of information provided by LLMs, and the ability of GenAI to displace human workers.

To mitigate these risks, you as a business leader need to ensure your team is ready for AI implementation. Promote a tech-savvy mindset, share knowledge of the latest technologies, encourage employees to use generative AI in their routine work, and develop ethical frameworks to ensure the responsible use of artificial intelligence. Also, before integrating GenAI into your software, consider security measures to protect your data, and augment your team with specialists who have specific expertise to implement AI models in your solutions.

Overall, generative AI’s meaning for business leaders lies in the opportunity to accelerate their internal operations and align with evolving customer needs. We’re sure that the future of generative AI is bright and that this technology is not going anywhere, so think of its implementation as a long-term journey. Develop technical fluency, promote responsible use of GenAI within your team, take small steps towards automating your business processes, and bring new value to the world with your AI-powered products and services.

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