How Generative AI Enables Partners to Accelerate Development, Innovation

Before we talk about how the partners ecosystem is using, deploying, investing in, and even protecting firms from generative AI, it’s a good idea to get us all on the same page regarding just what this technology is and how it works.

At the highest level, generative AI is a type of artificial intelligence (AI) that involves training a machine learning model to create or refresh content that is similar to or inspired by existing data. Generative AI models can create almost anything — from text to images to music to video and even 3D models.

Generative AI algorithms typically use a form of deep learning called generative adversarial networks (GANs) or variational autoencoders (VAEs). GANs consist of two neural networks: a generator that creates new data, and a discriminator that evaluates whether the generated data is realistic. VAEs use a different approach by encoding input data into a low-dimensional latent space and then decoding it back into new data. These two approaches are valuable but often applied in different use cases. The end result is newly-generated text, code, video, visuals, designs, and more.

While generative AI has many applications, including in art and design, content creation, marketing, hiring, and even medicine, it also raises concerns about potential misuse, such as creating fake news, flawed data, or deepfakes.

Now that we have reviewed the basics, I’d like to talk about how this revolutionary technology can impact partners ecosystems.

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How Generative AI Can Be Used by Technology Partners

First, it is important to note that as new technology, generative AI’s impact on the channel is more limited now than it will be in a few short years. That said, the impact is being felt in several ways.

One of generative AI’s key benefits is enabling companies to create new products and services that were previously impossible to develop using traditional programming methods. For example, as a technology ecosystem player in the past, you could not have enough programming capacity to customize applications for every customer or even for every industry.

With generative AI, that has changed. Generative AI can be used by a partner to recreate common code with configurations for each customer, if needed; then, the partner simply needs to check the code for accuracy. This saves hundreds, if not thousands, of programming hours and allows development of bespoke applications with limited programming investment. That’s truly a game changer.

With generative AI, companies can now train models to generate content or data that can be used to create products or services. For example, a tech partner could use generative AI to create unique designs for common processes or services or to generate personalized services for customers’ contact centers or websites; all without having to invest in customization.

Generative AI is also enabling partners to automate complex tasks that previously required human expertise. For example, many partners are starting to use generative AI as a help desk supplement by enabling their chat function to be “staffed” by AI, which can more easily find answers to common problems than earlier-generation chatbots, thereby reducing the need for human interaction.

Additionally, generative AI is creating new opportunities for companies to collaborate in the development of new products and services. For example, a company that specializes in generative AI for healthcare could partner with a company that produces healthcare software to create a new product that uses AI-generated healthcare analysis, records management, or diagnostic support. This creates an entirely new ecosystem of partners dedicated to specific solutions in vertical markets.

As a result of these developments, the technology partners ecosystem is expanding to include a new generation of companies that specialize in developing generative AI models and applications. These companies are partnering with traditional technology vendors to integrate their AI tech into existing systems and processes.

Finally, partners are beginning to use generative AI to find risks for specific use cases such as code mapping and code analysis, as well as risk management and a plethora of other applications.

Conclusion

Overall, generative AI is reshaping the technology partners ecosystem by creating new opportunities for collaboration and innovation and enabling companies to create new products and services that were previously impossible to develop using traditional programming methods. While we’re at the very beginning of the curve, this technology offers considerable opportunities for the technology ecosystem.

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