Oliver Gudgeon (oli

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Hey, all, we're running an event for the community on LinkedIn Live on 16 March. The goal is to help you fast track your intelligent automation use cases.

We'll be giving away some super useful frameworks/docs that we use regularly with clients, too. If you're responsible for implementing intelligent automation at your organisation, this is not one to miss.

Intelligent automation: 3 steps to fast track your use cases | LinkedIn

linkedin.com

If you’re an automation leader, this webinar will show you how to go from a rough solution concept to a tangible business outcome in three simple steps. Rainbird is a leading intelligent automatio...

Liked by Ian Barker and 1 other

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Posted last year

Sharing a breakdown of automated AML for banks that I wrote with (a lot of) help from our in-house financial services guru Geoff Hutton. 🙏

Written to help AML Systems Leads, Programme Directors, Project Managers, Transformation Managers at banks (and their wider teams) get to know more about the intelligent automation platform approach to automated AML.

Automated AML for banks—and why explainability matters | Rainbird Technologies

rainbird.ai

This blog post explains what automated AML means, three ways banks can approach it, and why explainability is so important.

Liked by Andrew Cassely

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Automation Insights

Posted last year

Insightful article from Wayne Butterfield at ISG.

"Once you start your journey towards using robotic process automation (RPA), you see that the automation you use – while helpful – isn’t intelligent."

Where to focus your automation efforts in 2022 - The AI Journal

aijourn.com

There’s always a lot of chatter about the next great innovative use of automation. While it’s appropriate for businesses to have their sights set on the horizon, sometimes it can be difficult to kn...

Liked by George Westlake

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Automation Insights

Posted 2 years ago

This caught my eye on Twitter—an interesting point of view from a machine learning thought leader.

It doesn't really matter what machine learning technique you use; a solution that doesn't require machine learning is probably always better.
— Santiago (@svpino) September 5, 2021

Liked by Andrew Cassely and 1 other

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Automation Insights

Posted 2 years ago

The UK gov's Office for Artificial Intelligence and the Department for Digital, Culture, Media & Sport has published a new report (prepared by EY): "Data foundations and AI adoption in the UK private and third sectors". They surveyed almost 400 firms and conducted 26 interviews with business leaders in organisations that vary by industry/size/location. The report shows how AI adoption varies by sector.

Here are some key findings:

- 90% of organisations have either a data strategy or data-related initiatives
- data foundations have been widely adopted, albeit slightly less so in third sector
- the 2 biggest challenges to data foundation adoption are existing infrastructure and lack of skilled personnel
- 27% of organisations have implemented AI
- 38% of organisations are getting ready to implement AI
- 33% of organisations have not adopted AI/don't plan to
- in the private sector, 90% of large organisations plan to or have adopted AI
- you're more likely to have adopted AI if you are in the finance sector, if you are a large organisation and you are less than 10 years old

6 key findings from the Data foundations and AI adoption in the UK private and third sectors report

gov.uk

Liked by James Duez and 5 others

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Automation Insights

Posted 2 years ago

A new thought-provoking article from Andrew Ng (former head of Google Brain) was published in HBR last week.

One of the most interesting points for me was where he argues that businesses should take a "data-centric mindset" and let subject matter experts (SMEs) be in charge of creating AI systems.

AI Doesn’t Have to Be Too Complicated or Expensive for Your Business

hbr.org

Most companies don’t have a clear path to success. But that might change with a new, data-centric approach to AI.

Liked by George Westlake and 2 others

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Automation Insights

Posted 2 years ago

There's a new article in Forbes by Pascal Bornet — some big numbers and claims, but interesting nonetheless.

He says intelligent automation could save around $10trn per year (assuming 100% effectiveness) — that's 1/2 of US GDP.

Some key points:

- IA is best placed to mitigate 3 types of losses: 1. fraud/financial crime 2. mistakes 3. employee accident/illness
- IA could save $5trn in fraud losses
- IA could save $1.068 in error losses
- IA could save $3trn in accident/illness losses

Council Post: How Intelligent Automation Could Help Avoid Trillions In Losses Per Year

forbes.com

The potential impact on our world could be enormous.

Liked by Timi Olotu and 3 others

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Oliver Gudgeon 150 Content Writer @ Rainbird

Do you have questions for Oliver Gudgeon?

Oliver Gudgeon
150
Content Writer @ Rainbird