The current state of AI, despite the relevant infancy of the tools, showcases promising potential. While human assistance is still needed, the convergence of chat UI and large language models allows users to ask for what they want in a natural language, and the technology is growing intelligent enough to respond or even take action.
New, game-changing technologies have emerged in the ever-changing field of software engineering as a result of the relentless search for efficiency and creativity. Platform engineering, AI coding assistants, and AI-augmented software engineering (AIASE) are predicted to achieve widespread acceptance in the next 2-5 years, according to the Gartner, Inc. Hype Cycle for Software Engineering, 2023. When it comes to Quality Assurance, software testing is one area where Chat GPT is predicted to thrive.
In recent years, governments across the globe have recognized the transformative potential of artificial intelligence (AI) and have embarked on initiatives to harness this technology to drive innovation and serve their citizens more effectively. These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm.
Commercializing an AI-based product requires turning technology into a marketable product, navigating challenges from development to market entry. Appealing to enterprise buyers is crucial for sustainable, continuous growth, as their interest not only validates your product’s value but also lays the foundation for long-term success and scalability. More specifically, the larger the businesses of your potential customers are, the more of a monopoly your product likely has in the market.
The misconception that product led growth implies a business neglects sales couldn’t be further from the truth. In reality, product led growth (PLG) involves integrating sales later in the customer journey, placing the purchasing power back in the hands of your users. This self-service approach is highly effective, especially when paired with insightful user data to streamline and target growth. For AI-centric companies, this product-led strategy serves as a fundamental pillar for success.
