The future of AI is dynamic and multi-faceted. In this episode of the Data Futurology podcast, we are thrilled to welcome Nikita Atkins, the Artificial Intelligence Executive at NCS Australia. With NCS being one of the leading voices in AI, both in the APAC region and globally, Nikita has more than a few insights to share about the future of the technology and its most exciting use cases.

We start by talking about low code/no code and how, by embracing that and enhancing it with AI, an organisation can shift their data science team away from “run-rate” models and tasks to instead focus on the highest value items.

From there, we talk about data cleaning and pipelines, before moving on to some of the exciting innovations that are coming to the AI space – how will AI assist in rebuilding digital trust after so many high-profile cyber breaches have shaken the confidence of Australian consumers? How can AI play a role in enhancing the sustainability credentials of organisations? And what are new concepts like AI ops and Explainable AI, and how is NCS set up to be a pioneer in this space?

This is a far-reaching and in-depth interview, you’ll get a good sense of how organisations will be transforming their AI environments in the years ahead.

Don’t forget! NCS will be at the Data Futurology Advancing AI conference in Melbourne in May. Be sure to come up and speak to Nikita and his team!

Connect with Nikita: https://www.linkedin.com/in/nikitaatkins/

Learn more about NCS: https://www.ncs.co

See NCS at Advancing AI Melbourne: https://www.datafuturology.com/advancing-ai-melbourne

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

WHAT WE DISCUSSED

00:00 Introducing Nikita Atkins and the topics for the podcast.

1:04 Nikita’s background, his role at NCS, and a company overview.

4:16 On the topic of generative AI – what’s behind the interest and excitement in this area?

5:43 How generative AI tools can be effectively used in the enterprise.

9:46 On the subject of AI and low code/no code – how can organisations implement AI in a way that can enhance this area?

12:20 What should organisations be thinking about in terms of governance or deployment challenges with regard to low code/no code?

15:20 In terms of data cleansing, do we get better outcomes from better quality data and better structured model data?

18:36 Data pipelines are a critical need for any business working with data – what role does automation have to play?

23:15 The advantages of standardising data collection.

25:56 The emergence of and benefits behind AI ops.

29:36 NCS and sustainability – how can data be part of the solution?

35:17 Digital trust – in the wake of so many cyber breaches, what can enterprises do to earn the respect of customers back?

38:05 The concept of Explainable AI – what is it, and why is it a focus for NCS?

EPISODE HIGHLIGHTS

“One of the key things that we see more, particularly those organisations that are very mature in data science, is that they are still making interesting choices, where data scientists still collect the same raw data in different ways. They're still cleaning it in different ways. And then they're doing ML. What we’re looking at is whether we can actually automate that process.”

“80% of scientists will admit to you that they don't like doing data cleansing. Well, let's automate that, standardise that and let them do what they do best."

“Some of our big clients have excellent science teams. But the problem is data scientists are not the cheapest people resources around. So a lot of organisations may have 10, 15, and perhaps as many as 50 data scientists. But if you take the power of low code, and you give that to the broader business, then you're unlocking the power of numbers.”

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