About

One government department recently held a fiftieth birthday party for its core ERP system. As we all recognise, dispensing with such systems takes billions of pounds and many years of software development. In 2023, the Treasury has allocated seven billion pounds to address this problem across UK government departments. Cloud has provided a more agile base to support such systems, but until recently, it has not addressed the central issue of legacy migration.

According to AWS and CISCO, the inclusion of powerful tools such as generative AI on their cloud platform could provide a radical shortcut for legacy migration, leading to more flexible and adaptive solutions to serve the public. In this evening event, AWS and CISCO will discuss this major challenge. Issues include:
 
  • Could the cloud provide an effective pathway for legacy migration and at what cost?
  • Will generative AI be the ‘secret sauce’ for legacy migration and how might this work?
  • What are the security issues that emerge once data is firmly rooted within the public cloud, and how can these be mitigated?
  • How can we avoid legacy issues emerging from a multi-cloud environment in the
    future?
AWS and CISCO invite you to a discussion dinner in London on the 1st November, starting at 18.30. Leaders from Central Government will introduce the discussion. Roger Camrass of CIONET will be your host, and as with all CIONET events, this meeting of minds will help empower you in your digital leadership role.
Meet the Speakers

Speakers

Find out more about the speakers

Roger Camrass_Research Director_CIONET UK

Roger Camrass

Research Director

CIONET
Explore the program

Program

Please note that timings are in GMT.

 


 

November 1
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The Royal Horseguards Hotel, 66 Victoria Street, London


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Venue

In a landmark Victorian building that was once the Secret Service's HQ, this posh hotel is a 2-minute walk from Embankment Underground Station and a 7-minute walk from the National Gallery.

The Royal Horseguards Hotel, 66 Victoria Street, London

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