Organisations must focus on getting the data fabric in place or risk AI project failure.

As more enterprises look to implement AI projects in 2023 to increase productivity, gain better insights and have the ability to make more accurate predictions regarding strategic business decisions, the challenge will be for traditional enterprises to establish a robust data framework that will allow their organisations to leverage data effectively for AI purposes. Organisations must have the correct data Infrastructure Architecture (IA) to succeed. 

AI white-labelling levels the playing field for traditional enterprises.

In 2023, as AI becomes a “need to have” versus a “nice to have,” the ability for an organisation to utilise “white-label” AI to create configurable and customisable solutions can lead to a capability differentiator for enterprises, allowing for these companies to gain an AI-edge over their competitors and peers. Newer products that allow enterprises to embed AI processes into their existing products– products that harness Computer Vision, Machine Learning (ML), and Natural Language Processing (NLP) – will power companies with AI at the back end to deliver a smarter, enhanced, and seamless experience in the solution’s native environment for end-users.

A centre of excellence is vital for AI implementation - getting the right people and expertise in one place.

COEs can help an organisation implement and succeed in its AI journey in the following ways:

• Creating the right team of dedicated experts from multiple disciplines and departments 
• Provide the basis for organising, analysing, cleaning, and identifying the right data silos so that an AI implementation can commence.
• Drive digital class transformation with the COE’s buy-in of the AI goal so that the organisation can make changes for the better.

ERP systems need to be “AI-ified.” 

While ERP systems are strategic for entering, storing, and tracking data related to various business transactions, CIOs, COOs, and business analysis teams have struggled over decades to extract, transform, and load data from ERP systems and utilise it for AI/ML applications. In 2023, the market is starting to support the concept of AI micro-products or toolkits that can connect to ERP systems through middleware. The middleware can then feed into the leading AI platform to develop, select, and deploy ML models to provide highly accurate predictions and forecasting.  

Natural Language Processing and Computer Vision will play an important role.

Enterprise adoption of automation of processes involving text or voice data using Natural Language Processing (NLP) and Computer Vision (CV) technologies will significantly enhance in 2023. While designing a solution, recommendations and search engines are powerful tools for bringing relevant content to visibility. Based on wide data- data from multiple sources, AI can also help predict business outcomes, allowing companies to make rapid decisions. In addition, NLP-based systems help organisations to meet regulatory compliance requirements.

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