Practical, sourced writing on getting real results from AI. New posts every Monday, Wednesday and Friday.
AI engines can only cite pages they can fetch, read and trust. Allow AI search crawlers, serve full HTML without relying on JavaScript, add structured data, publish an llms.txt file, keep entity details consistent, submit to Bing via IndexNow, and show clear authorship and update dates.
CPA firms get the quickest return from AI on high-volume, low-judgment work. Start with document collection and reminders, data extraction from client documents, engagement and intake, routine client emails, meeting notes, internal knowledge search, first-draft workpapers and review checklists. Keep professional judgment and sign-off with your team.
AI voice agents handle repetitive, predictable calls best. After-hours answering, appointment booking and rescheduling, lead qualification, FAQs, order status, intake, reminders, overflow during busy periods and call routing are the strongest use cases. Complaints, emergencies and complex sales should still go to a person.
In today's data-driven business landscape, organizations are drowning in information while thirsting for insights. Enterprise search has evolved from simple keyword matching to sophisticated AI-powered knowledge discovery systems that can understand context, intent, and relationships within vast data repositories.
Document processing has long been one of the most time-consuming and error-prone activities in business operations. From processing invoices and contracts to analyzing reports and compliance documents, organizations worldwide handle billions of documents annually.
The concept of AI-powered business assistants has evolved from science fiction to business reality. Enterprise copilots represent the next generation of workplace productivity tools, combining advanced artificial intelligence with deep business context to provide intelligent assistance across a wide range of tasks and processes.
The traditional approach to business intelligence and data analytics has created a significant barrier between data and decision-makers. Complex query languages, dashboard configurations, and technical expertise requirements have limited data access to a select few within organizations.
In the era of big data, organizations are discovering that the value of information lies not just in individual data points, but in the relationships and connections between them. Knowledge graphs represent a revolutionary approach to data organization and analysis, creating interconnected webs of information that mirror how humans naturally understand and process knowledge.
A 30-minute call with a consultant, not a sales rep. You leave with at least one concrete next step, whether or not we work together.