VENTURE CAPITAL
“ IT ONLY ADDS VALUE IF IT ’ S BEING USED CORRECTLY . JUST HAVING “ AI ” ISN ’ T A VALUE ADD ON ITS OWN ”
ROBERT HARTLEY ACII AND CO-FOUNDER , DINGHY
productivity , all of which further personalise the customer experience .”
Kuhn says the technology is essential because it drives innovation where it is needed most . “ This also increases efficiency and gives employees back time that can be spent on tasks that require a human touch , which is really important at this busy time .”
However , he points out that guidance is required in terms of selecting the correct solutions .
“ Companies need the right set of tools and processes to foster this low-cost , high-value experimentation . This is where low-code can save the day . Acting as the glue that keeps these technologies together , low-code enables cross-functional teams of professional developers , citizen developers , and functional staff to easily collaborate and connect multiple applications for end-to-end solutions . This means AI initiatives can get off the ground in a fraction of the time without the need for additional resources .”
Startups and AI While startups don ’ t necessarily require AI to attract investors , there are elements of AI that generate interest from potential
funders . Oliver Richards , partner at MMC Ventures , leads early-stage investments at Seed and Series A and manages a portfolio that includes a range of transformative technology businesses in fintech and B2B enterprise SaaS .
He recently led MMC ' s investments into Yulife , Snowplow , Copper and TreasurySpring and recent investments into his portfolio including Safeguard Global and Peak AI .
He says , “ The current levels of VC excitement regarding modern AI generally relates to a set of techniques called machine learning ( ML ), where advances have been rapid and significant . ML is a sub-set of AI , enabling programs to learn through training , instead of being programmed with rules . By processing training data , machine learning systems provide results that improve with experience .”
Richards says the attraction of the technology lies in its broad use cases . “ ML can be applied to a wide variety of prediction and optimisation challenges ,