AI & Automation

For the small business owner, the issue is seldom an “AI problem”. It is a matter of workflow, and AI is there to address it provided the scope is right. The difference is worth noting: some 80% of AI projects come to nothing, and you will not see a bad model as the cause. More […]

You get the contract over email. Some one will download it, give it a new name and put it in front of legal. After you have waited and followed up, you get back a revision to pass on to finance, and the final version ends up in a shared drive that is not exactly trusted […]

You will find that the majority of teams don’t have an automation problem per se. They have a process issue and their automation is only serving to highlight it. An invoice sits there for a manual touch, a demo request comes in to an inbox, or some Zap goes quiet because a column was renamed […]

You will not find most enterprise workflow automation projects failing in the engine. They fail in the seams: with a legacy system that has the data, an approval sitting in some inbox, or an exception you did not put in your plans. From the outside, adoption appears to be in good health. Some 70 to […]

You will hear small business owners ask which chatbot to buy. It is the first question on their lips, but also the wrong one to begin with. You should be asking what you need the bot to do in a given corner of your operation: are you looking to capture leads, book an appointment, offload […]

The hardest part of buying generative AI is not picking the model. It is finding a partner who will tell you when your idea is too broad, your data is not ready, and a workflow change would beat the build. That kind of judgment is rare, and it is exactly what separates a generative AI […]

Do the numbers for a senior AI engineer in New York and you are looking at $350,000 to $500,000 fully loaded. Put in the salary, benefits, recruiter fees, equipment and management overhead and that is what it runs. Then look at Clarista’s 2026 compensation analysis: put the same person on staff in India, Eastern Europe […]

Most AI engagements do not fail because the model was wrong. They fail before the model is chosen. The business problem is fuzzy, the data sits in three systems nobody owns, and the launch plan stops at the demo. Stanford’s 2026 AI Index reports that 88% of organizations now use AI in some form, yet […]

You will see a wide variance in the numbers when you look at enterprise AI. Vendors will tell you their success rate is over 60 per cent, but an independent audit of such projects puts the figure for those that hit business objectives on the first try at between 20 and 35 per cent. That […]