Top Generative AI Solutions: Scaling & Best Practices

According to the latest State of AI report by Salesforce, 86% of IT leaders expect generative AI to play a prominent role in their organizations. [1] Although the technology has only been in existence for less than a decade, 32% of organizations have already started to leverage its analytics capabilities, with most of them reporting significant benefits. [2] By employing the right tools, organizations can streamline content creation, improve manufacturing processes, and develop innovative solutions, paving the way for greater creativity and efficiency.

This guide will explore the potential benefits of using generative AI to drive business value and some of the most notable generative AI tools empowering businesses across the board.

What is Generative AI?

Generative AI is a subset of artificial intelligence (AI) that focuses on training machine learning models to produce original, creative content. Essentially, Gen AI can learn from existing data, such as text, images, and videos, to generate new, realistic data that reflects the characteristics of the original data used to train it.

The technology achieves this by using complex neural networks and algorithms that enable it to understand patterns and produce outputs that closely resemble human creativity.

Generative AI has evolved immensely over the past few years. Not so long ago, most businesses relied on conversational AI to facilitate automated communication with their customers. Conversational AI allows humans to communicate with machines through machine learning and natural language processing (NLP) technologies.

Although conversational AI allows virtual agents like chatbots to understand the meaning and sentiment behind human input and provide appropriate responses, it’s quite limited in scope. This is because these responses have to be created as dialogue flows, which requires a tremendous amount of time and skilled personnel.

Generative AI, on the other hand, takes a different approach in the way it processes input to provide an appropriate response. By leveraging information contained in the training data, Gen AI models can understand and generate content in a broader context. This means that, unlike their counterparts, Gen AI models are not limited to a predetermined dialogue flow, enabling them to facilitate greater customer engagement across a myriad of topics.

How will Generative AI contribute to business value?

Generative AI has lots of benefits and potential applications that could drive business value immensely. This is even more notable with foundational models like ChatGPT, which offer a wholesome, general-purpose approach that can facilitate various use cases, including content creation, content improvement, synthetic data generation, and widespread automation.

Gen AI is more notable when it comes to automation in relation to growing business value. When leveraged correctly, Generative AI tools can augment humans in repetitive processes or autonomously execute business IT processes.

As a result, businesses that leverage Generative AI tools could see significant improvements in customer experience, product development, and employee productivity.

Other notable ways generative AI can contribute to business value include:

Broader revenue opportunities

Gen AI is poised to revolutionize product development. By simply adjusting a few metrics within the original product design and adjusting model parameters, product design teams can create several versions of the same product, enabling them to choose the most favorable design based on project requirements.

Additionally, generative AI tools can help in material selection based on several factors, including cost and performance specifications. When prompted correctly, Gen AI algorithms can predict how different materials will perform based on their physical properties, making it easier to predict production costs and potentially minimize them by selecting cheaper, better-performing materials.

Besides its vast potential to revolutionize product development, Gen AI can also help create new revenue channels. By analyzing customer data through analytics, generative AI tools can effectively identify patterns, preferences, and potential opportunities businesses can pursue to optimize revenue streams and even create new ones.

Gen AI has also proven to be effective in analyzing and predicting market trends. This has given rise to AI-powered dynamic pricing models that can optimize prices in real-time based on demand, customer behavior, competition, and maximizing profits. Ultimately, this helps ensure a competitive advantage without negatively impacting customer satisfaction.

Cost management and productivity improvement opportunities

Simple, repetitive jobs like drafting and editing documents, images, and other media are some of the greatest hindrances to improving productivity. In fact, it is estimated that employees only spend 39% of their day on on-role tasks, which translates to about 19 workdays every year wasted on recurring tasks. [3]

Generative AI tools can augment human workers’ ability to draft and edit text documents and other media. They can also help in content creation, summarization, and classification, not to mention their ability to generate and verify software code.

As generative AI utilization across organizations intensifies, employees will soon be distinguished by their ability to conceive, execute, and refine their ideas using AI. Ultimately, this symbiotic relationship will significantly improve the proficiency, productivity, and competency of workers across the board.

Risk mitigation and sustainability

Organizations lose up to 5% of their revenue to fraud each year. What’s even more concerning is some of these threats can remain active for 12 months before they’re detected. [4]

Fortunately, generative AI analytics capabilities are not just limited to analyzing customer and business process data. They can also be applied to a business’s financial data, providing a deeper and broader understanding of the data. Ultimately, this can help identify potential risks such as fraud and faulty software code, thus minimizing fraud-related losses.

As organizations across the world become more aware of the potential implications of their manufacturing practices on the environment, many are gearing towards boosting sustainability. In fact, sustainability is one of the biggest concerns for 65% of businesses across all regions. [5]

While taking proactive approaches like using sustainable materials like recyclable and lower-emitting materials may improve the chances of an organization reaching its sustainability goals, there are still a myriad of factors that may go unnoticed. Additionally, many governments across the world are enacting laws and regulations aimed at boosting sustainability. Any business found in violation of these regulations may face heavy penalties, including fines and license suspensions.

However, with generative AI, companies can analyze their workflows and production practices to determine potential areas of improvement. By doing so, organizations can also improve their compliance standards and reduce the possibility of future compliance issues by embedding sustainability into their decision-making process.

Role of Generative AI in various industries

Generative AI has the potential to revolutionize nearly every aspect of business. Some of the most notable use cases of generative AI in business include:

• Content Creation

Most businesses have some form of online presence, mainly in the form of websites and social media accounts. This is not accounting for the nearly 64% of small businesses that use email marketing to reach their customers. [6]

Based on these factors alone, it’s clear to see that many businesses across all sectors have varying content creation needs. With generative AI, businesses can effectively automate content generation, leading to more streamlined workflows and a remarkable reduction in the time spent creating content.

• Software Development

It takes about 4 to 9 months to develop functional software. The timeline might extend beyond this scope based on several factors including project requirements and the availability of skilled personnel.

However, according to a recent McKinsey report, software developers can complete tasks up to two times faster with generative AI.[7] The accelerated development process can be attributed to generative AI capabilities to generate code snippets, suggest effective solutions to coding challenges, and improve software testing by identifying defects in the code.

• Healthcare

The generative AI market in healthcare is expected to reach $22.1 billion by the end of 2032, up from $1.8 billion in 2023, growing at a CAGR of 32.6% over the analysis period. [8] This unprecedented growth comes as no surprise, considering the potential applications of generative AI in the healthcare sector.

For instance, medical experts can use generative AI to analyze medical images, diagnose illnesses, and predict patient outcomes. According to a recent study, radiologists using generative AI for image analysis reported a 20% improvement in accuracy when detecting subtle anomalies. This clearly shows the potential of AI to provide timely and accurate diagnosis.

• Art and Design

The art and design sector has seen considerable utilization of generative AI in the creation of unique visual art, designs, and illustrations. A recent study found that using generative AI in the design process led to an increase in the number of eye-catching and innovative design concepts [9].

The 10 best generative AI solutions

Finding a reliable technology partner can be quite overwhelming. Despite the wide availability of generative AI models, some are better suited for specific tasks than others, thus necessitating the need to carefully evaluate your choices before making a final decision.

In this section, we explore 10 of the best generative AI solutions that are empowering businesses of all sizes and shaping the technology’s present and future.

GPT 3.5 (ChatGPT free)

Released in November 2022, OpenAI’s ChatGPT is based on a cutting-edge Large Language Model (LLM) – GPT 3.5 – known for its remarkable ability to generate human-like text. The model showcases remarkable versatility when it comes to crafting natural conversations, elaborating queries, and generating text in creative writing tasks.

Its impressive capabilities in natural language processing, understanding, and generation make it especially suitable for a myriad of use cases including content generation, customer support bots, author brainstorming, and much more.

Key features:

• Human-like language generation
• Natural and authentic conversations
• Remarkable ability to understand queries and responses in contextually relevant ways
• Detailed and insightful answers to diverse queries
• Valuable suggestions and support for creative writing endeavors

GitHub CoPilot

GitHub Copilot is arguably one of the best generative AI tools for coding. The model offers various collaborative features and integrations with popular code editors. As a code-focused LLM-driven solution, GitHub Copilot utilizes natural language processing technology to generate code snippets, context-based guidance, and explanations.

As such, the model can significantly enhance developer productivity and learning. This impressive versatility also makes it suitable for a wide range of beneficial use cases, including accelerating the coding process, facilitating learning, elevating code quality through effective defect detection, and facilitating learning by helping programmers learn new programming concepts.

On the downside, you may need to apply some vigilance when utilizing the model, as some generated code may need further polishing. It also heavily relies on external APIs for suggestions, which might complicate setup and utilization for inexperienced users.

Key features:

• Seamless integration with popular code editors
• Ability to adapt to individual developer preferences by learning from usage patterns
• Instant, relevant suggestions for code completion
• A diverse range of programming language support
• Ability to generate explanations and contextual information along with code snippets

Scribe

Scribe is an AI writing assistant that’s specially designed to streamline content generation. It shows remarkable prowess in crafting reports, summarizing articles, and aiding in academic writing.

This has made it especially popular among students, journalists, and other professionals who use it for research and content generation.

Key features:

• The ability to generate content in diverse styles and formats
• Dedicated AI writing assistant
• Seamless text generation, summarization, and documentation
• Simplified documentation of complex tasks

GPT-4 (ChatGPT Plus)

GPT-4 is the latest addition to OpenAI’s GPT family. Unlike ChatGPT in its free version, GPT-4 has multimodal capabilities, which means it can process both text and image inputs. Like its predecessors, GPT-4 has remarkable capabilities in content generation, making it an invaluable tool for marketers, writers, and editors.

It is important to note that GPT-4 was trained on a larger corpus of data than its predecessors, which means it can generate higher-quality content across various domains and handle more nuanced queries. [10]

Key features:

• Ability to generate high-quality text across various domains
• Ability to generate natural, human-like content
• Greater accuracy in tackling more intricate queries
• Ability to produce coherent and nuanced responses
• Allows users to steer the style, tone, and other specifics of generated text

Cohere Generate

Cohere Generate has proven to be quite effective in crafting dynamic dialogue systems that enhance user engagement. The model leverages NLP technology to generate personalized content, facilitating a wide variety of use cases ranging from virtual agents to custom email generation.

Key features:

• Ability to handle diverse natural language tasks
• Proficiency in creating personalized email content
• Seamless creation of interactive conversational AI agents
• Ability to deliver human-like responses, thus facilitating authentic conversations

AlphaCode

AlphaCode is a dynamic coding assistant that leverages gen AI to perform a myriad of coding tasks. The model excels in various use cases including bug resolution, code generation, task automation, and suggesting optimal programming solutions.

However, despite its efficiency in mitigating coding errors and fostering coding proficiency, you may need to perform further polishing in intricate tasks since the model relies on established programming patterns.

Key features:

• Leverages advanced Gen AI for coding assistance
• Real-time code suggestions and fixes
• Supports numerous programming languages and paradigms
• Provides code optimization solutions

Gemini (previously Bard)

Google Gemini (p. Bard) is a revolutionary chatbot and content-generation tool. Developed as Google’s answer to ChatGPT, Bard leverages LaMDA, a transformer-based model to generate natural, human-like content.

Bard can draft several forms of written content, including blog posts, articles, and creative writing pieces. It can also aid in code generation and provide helpful suggestions for programming-related queries.

Key features:

• Accessible via individual Google accounts
• Provides assistance in software development and programming-related tasks
• Leverages the power of LaMDA to generate human-like content

Claude

Developed by Anthropic, Claude is a cutting-edge AI assistant capable of handling extensive data processing tasks, automating complex workflows, and engaging in natural, fluent conversations.

Key features:

• Can handle extensive data processing tasks
• Ability to engage in natural and fluent conversations
• Seamless adaptation to user feedback
• Multilingual proficiency

DALL-E2

Dall-E2 is a state-of-the-art image generation tool. It can translate text into captivating visuals, enabling designers and artists to explore new realms of reality. The model can also accommodate various image styles and genres, enabling it to produce unique artwork and custom images.

Key features:

• Leverages Gen AI technology for image synthesis
• Can accommodate a wide range of image styles and genres
• Ability to transform textual prompts into intricate, captivating images

Duet AI

Duet AI is a cutting-edge writing assistant poised to revolutionize Google Workspace. The model leverages LLM capabilities to generate and summarize content and integrates seamlessly with popular Google applications.

That said, the model is still in beta but shows significant potential to streamline workflows within Google applications. According to the company, you’ll soon be able to generate content, summarize text, and rewrite content within familiar tools like Google Docs, Gmail, and Google Meet.

Key features:

• Leverages Gen AI to facilitate content generation
• Can enable users to create intelligent business applications
• Can generate images based on textual prompts
• AI-driven code assistance for users on the cloud

Final thoughts

Generative AI is revolutionizing how businesses operate. Tedious tasks like content generation and summarization that were previously limited to the human workforce can now be augmented and automated, thus improving workflows and productivity.

As more generative AI tools hit the market, we’re poised to see more specialized tools capable of handling more intricate tasks. However, there are still some challenges with the technology, including the potential for bias, that need to be addressed before these tools can see widespread usage in real-world use cases.

References

[1] Salesforce.com. As IT Demands Rise, New Data Reveals Importance of Automation and Generative AI. URL:
https://www.salesforce.com/news/stories/trends-in-IT. Accessed on April 24, 2024
[2] Topdigital.agency. Generative AI Use Cases Every Company Should Consider. URL:
https://topdigital.agency/generative-ai-use-cases-every-company-should-consider. Accessed on April 24, 2024
[3] Information-age.com. Productivity pains: 90% of workers burdened with repetitive tasks. URL:
https://www.information-age.com/productivity-pains-90-workers-repetitive-tasks-7347/. Accessed on April 24, 2024
[4] Snappt.com. Average Cost of Fraud for Businesses. URL:
https://tiny.pl/dw4dx. Accessed on April 24, 2024
[5] Forbes.com. The Future Of Corporate Sustainability—Even In A Tough Economy. URL:
https://tiny.pl/dw4d7. Accessed on April 24, 2024
[6] Luisazhou.com. Email Marketing ROI Statistics: The Ultimate List in 2024. URL:
https://tiny.pl/dw4dd. Accessed on April 24, 2024
[7] Mckinsey. com. Unleashing developer productivity with generative AI. URL: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/unleashing-developer-productivity-with-generative-ai. Accessed on April 25, 2024
[8] Gminsights.com. Generative AI Health Market Size. URL: https://www.gminsights.com/industry-analysis/generative-ai-in-healthcare-market,Accessed on April 25, 2024
[9] Researchgate.net. The Effects of Generative AI on Design Fixation and Divergent Thinking
URL: https://www.researchgate.net/publication/378302717_The_Effects_of_Generative_AI_on_Design_Fixation_and_Divergent_Thinking, Accessed on April 24, 2024
[10] Openai.com. GPT-4. URL:
https://openai.com/research/gpt-4,Accessed on April 25, 2024