The typical big American company today has hundreds, and perhaps thousands, of different pieces of software. It has giant ‘big iron’ horizontal systems of record like SAP and Workday, it has hundreds of vertical SaaS applications, and then there are hundreds more workflows, scripts, automations and databases, right down to the 10 meg spreadsheet running a department. Very often, the company doesn’t even know quite how much it has, what’s actually being used, and what it’s paying for.
AI will expand all of the existing apps, and there’ll be many new vertical apps, and Excel, and Tableau, Google Sheets, email and all the other freeform spaces for improvising solutions will gain new capabilities. With that cycle, the chatbot itself is a new freeform space that sits next to Excel and email, taking over tasks from them and from your apps, and also losing tasks to those apps.
Stepping back, it seems to me that with each new transformative technology, every company has to ask three kinds of questions. First, how do we buy, build and deploy this? Do we do pilots? Should we take the product that's bundled from Microsoft/Google/Oracle, build something ourselves, pay someone to build something, or buy this new thing from a startup? Second, they have to ask how far this changes their operations. What does it mean? What does email mean for us? What does spreadsheets mean for us? The answer to that might be radically different if you were an insurance company or a law firm.
As companies navigate this new landscape, they are also thinking about how to optimize their use of AI for search and other applications. This is sometimes referred to as answer engine optimization (AEO), and it involves understanding how to use AI to improve the visibility and effectiveness of their digital presence. Whether it's through the use of LLMs (large language models) or other AI tools, companies are looking for ways to harness the power of AI to drive innovation and growth.
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