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Putting Smart ERP into Action

Arthur Cole

One of the questions enterprise executives will have to ponder when unrolling or upgrading ERP platforms is how much intelligence it should have.

It seems there will be little choice when it comes to incorporating machine learning, chatbots and other forms of AI into ERP systems going forward, so the decision will come down to how to implement these technologies, how quickly and how to control them.

According to Priority Software CEO Andres Richter, AI is already being used in key ERP modules where it is boosting efficiency and productivity in a number of processes. In warehousing, for example, AI can test hundreds of demand forecasting models and then automatically adjust results based on variables like new product introduction, supply chain distribution, and changes in demand. Financial management is also getting a boost as bots are unleashed on repetitive accounting functions such as invoice categorization and monthly, quarterly and annual auditing.


In fact, says SAP’s Ivo Totev, organizations using cloud-based ERP services may already be using AI and not even know it. In an interview with TechRepublic, Totev says AI is being integrated into ERP and other platforms as a core capability, automating many existing manual processes and producing significant gains in productivity and turnaround. In this way, AI will likely become democratized across the IT landscape, providing all users with high levels of performance regardless of size or technological knowhow.

Still, says ZDNet’s Larry Dignan, someone will have to take responsibility for managing this technology, and in particular the algorithms that process data. In all but the most advanced tech firms, however, this knowledge is a rarity, which means the typical enterprise will be at the mercy of systems that, unlike the fixed hardware/software solutions of the past, will change and adapt to new situations in unpredictable ways. Even at the initial deployment, few vendors are providing transparency into their intelligent technologies or what kinds of biases may be lurking within their code.

But before we give in to the fear of runaway platforms doing who-knows-what with critical data, realize that nobody is going to knowingly release a solution that wreaks havoc on enterprise data processes – and if they do, they probably will not be around for very long. By and large, organizations will see significant gains from AI, most likely through the automated coordination of the multiple business units – manufacturing, sales, finance – that currently suffer from disjointed data flows and clerical errors.

At the same time, AI is proving highly adept at finding hidden patterns and relationships in data, particularly unstructured data, that could very well lead to all-new products, markets and even business models.

All of this will take time, of course. AI is not a magic-bullet solution that you power up to solve a specific, pre-defined problem. It has to learn how things work first and then implement the correct fix to make them faster, more accurate – in a word, better.

Ultimately, however, once this newest member of the team is up to speed, it should kick off a new era in enterprise productivity.

Arthur Cole writes about infrastructure for IT Business Edge. Cole has been covering the high-tech media and computing industries for more than 20 years, having served as editor of TV Technology, Video Technology News, Internet News and Multimedia Weekly. His contributions have appeared in Communications Today and Enterprise Networking Planet and as web content for numerous high-tech clients like TwinStrata and Carpathia. Follow Art on Twitter @acole602.

 


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