Generative AI tools are advancing rapidly, prompting you to decide whether to jump on board now or wait just a bit longer to see how the story unravels. While the saying "Good things come to those who wait" may ring true, there might not be many good things to share after waiting when the competitors are already far ahead. Generative AI has the potential to contribute $2.6 trillion to $4.4 trillion annually to the global economy, making this the right moment to seize market share. The question is, how can you determine its real value for your business?
The Surge and Ongoing Growth of AI
AI was already a hot topic, and since OpenAI launched ChatGPT in November 2022, interest in AI, especially generative AI tools, has skyrocketed. ChatGPT has become the fastest-growing app ever, acquiring 100 million monthly active users in just two months. At the time of writing, a bit over a week ago, OpenAI launched its GPT Store, where ChatGPT subscribers can access custom-built GPTs to find a genie for basically anything – say, a research paper analyzer, a fitness trainer, or a programming assistant. Here at Brightly, we have heard our enterprise clients grappling with the question of how to extract value from AI and generative AI tools. After all, chances are that many of their employees are already using generative AI tools to spark their imagination.
While early prototypes of hallucinating chatbots or image generators drawing twelve-fingered people may not always be convincing, the genie is not going to go back in the bottle. Our prediction is that, in a few years ahead, businesses will demonstrate how generative AI can enhance productivity or improve products and services to boost revenue. The key is for companies to start experimenting, trial the technology, and transition to production use.
According to a McKinsey report, generative AI could add $2.6 trillion to $4.4 trillion annually in value to the global economy. There is something to share for everyone brave enough to start experimenting early enough. The challenge is distinguishing value-driving opportunities from mere hype, and this is where Brightly’s AI Horizon framework comes into play.
AI Horizon: Identify your best AI use cases
Brightly’s AI Horizon framework is a workflow designed to help you pinpoint the most value-generating AI use cases. We have built several production-level AI and generative AI solutions with our clients, and together with your team, we identify the right curtains to open and stones to turn to find where the actual value of AI is hidden. The AI Horizon framework takes one to four months to run, depending on your needs, and comprises three modules.
- Coaching session: Brightly’s AI experts provide your team, board members, or other relevant stakeholders with basic or detailed knowledge tailored to your organization’s specific needs.
- Workshops: Facilitated by Brightly’s AI and service design experts, these workshops help identify where AI could bring the most value to your business. Typically, two workshops result in a prioritized roadmap of potential AI use cases.
- Proof of concept: Now, this module brings your ideas alive. After identifying where to start in the workshops, we implement a proof of concept for the chosen solution(s).
You can read more about the AI Horizon framework here or by contacting us.
A Proof of Concept is not enough for business value
In general, there are two ways to benefit from technology:
- Increase productivity, or
- gain new revenue through innovations.
Technology's potential becomes visible when integrated into your services, products, or processes. AI, like any technology, is a strategic asset to enhance your competitive advantage, and the real value comes when you move beyond proof of concepts. Brightly’s AI Horizon framework is an excellent way to start your AI journey.
In the AI Horizon framework, we focus on the big picture and your business context. After the AI Horizon, we still need to examine what's needed from your data and infrastructure to incorporate AI or generative AI solutions into your revenue-generating products or services. Determining the data for training your AI models and updating legacy infrastructure may be necessary to achieve business objectives. Additionally, implementing proper risk mitigation and data governance plans is crucial, as generative AI models pose risks such as bias or hallucination originating, for example, from defective training data or poorly working AI models.
This isn't to discourage you from seizing AI opportunities but to provide a realistic view of what to expect. After the initial idea, there are many steps to take to realize the business value of an AI solution. With our experience in building real-life AI solutions, we can guide you through every step of your AI journey, from establishing your data & AI strategy to educating your organization and building the end solutions.
