S5E1 - Manifesto for Change: How AXREM’s AI Group is Shaping Healthcare’s Future

In this episode of AXREM Insights, Melanie Johnson and Sally Edgington speak with Graham King, Solution Architect for Analyse AI and Convener of AXREM's AI Special Focus Group, and Ben Reed, Digital Services Business Manager at Siemens Healthineers and Vice Convener. They discuss the recently launched AI Manifesto, which outlines the group’s commitment to responsible innovation in healthcare. A key focus is on the need for scalable adoption of AI across the NHS while minimising duplication, standardising compliance processes, and addressing funding challenges. The conversation also highlights the synergy between AXREM’s AI and Imaging IT groups and the importance of collaboration across the industry to foster standardisation, improve workflows, and ultimately benefit patient care.

The guests emphasise the urgency of adopting AI technologies at scale to tackle growing diagnostic demands, clinician shortages, and rising volumes of imaging data. They reflect on the longstanding role of AI in radiology and explore new applications including large language models for reporting and predictive analytics for patient no-shows. Additionally, they discuss the value of AXREM membership, particularly for SMEs, through shared expertise, access to key stakeholders, and opportunities for partnership. The episode wraps up with a light-hearted discussion about time travel, revealing Graham’s curiosity about the past and Ben’s desire to leap into the future.

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Transcript

[00:00.000 --> 00:18.600]  Hello and welcome back to Series 5 of AXREM Insights. During Series 5, we will be showcasing
[00:18.600 --> 00:23.640]  all of AXREM's special focus groups, bringing you the most up-to-date news and information
[00:23.640 --> 00:28.480]  directly from the group. I'm Melanie Johnson and I'm here with Sally Edgington. Today we
[00:28.480 --> 00:34.560]  have the pleasure to be speaking to both Graham King, Solution Architect for Analyse AI and AXREM's
[00:34.560 --> 00:40.440]  AI Special Focus Group Convener, as well as Ben Reed, Digital Services Business Manager for
[00:40.440 --> 00:46.720]  Siemens Health and Ears and AXREM's AI Special Focus Group Vice Convener. Welcome Graham and
[00:46.720 --> 00:52.160]  Ben and thank you for being on our show today. Now let's start by handing over to you to tell
[00:52.160 --> 00:57.880]  us a little bit more about yourself and watch your story. Ben Reed, Business Manager at Siemens,
[00:58.600 --> 01:06.040]  our IT portfolio and I've been in this industry for 30 years this year, largely with Siemens.
[01:06.040 --> 01:10.440]  Everything from developer through implementer installations and now obviously selling and
[01:10.440 --> 01:15.480]  business management of IT solutions into the NHS and the private sector for the whole of GB and
[01:15.480 --> 01:21.560]  Ireland. Super, and Graham? Yeah, so I'm Graham King, Solution Architect for Analyse AI. I've
[01:21.560 --> 01:27.120]  been working there for three years plus. I've been in the world of AI and imaging for about seven
[01:27.120 --> 01:34.640]  years and then imaging and health interoperability for, oh golly, over 20 years now and IT for even
[01:34.640 --> 01:40.760]  longer than that. So I also share the AI Special Focus Group for AxRom and Ben helps me as Vice
[01:40.760 --> 01:45.800]  Chair or Vice Convener as I think we're supposed to call it. And so very active group with a lot
[01:45.800 --> 01:50.640]  of membership, growing membership and beginning to raise our profile across the community and
[01:50.680 --> 01:57.960]  across the industry. Thanks, Graham. And I think it would be great to start. Obviously, recently we
[01:57.960 --> 02:04.560]  launched the AI Manifesto for the group and this really does set out all of your kind of key
[02:04.560 --> 02:09.640]  priorities and calls to action. So if okay, if you could tell us a little bit more about the
[02:09.640 --> 02:17.600]  manifesto, that would be fantastic. Yeah, we wanted to cast the manifesto mostly as a statement of
[02:17.600 --> 02:24.040]  what our members will do to be responsible innovators and responsible introducers of new
[02:24.040 --> 02:28.440]  technology to the health service. There's always a worry about disruption when there's a new
[02:28.440 --> 02:33.280]  technology and never more so in healthcare where we don't want to upset, you know, existing care
[02:33.280 --> 02:39.120]  processes and where mistakes can have quite serious and far-reaching consequences, particularly if we
[02:39.120 --> 02:44.120]  consider the use of artificial intelligence solutions in any kind of screening program,
[02:44.280 --> 02:48.760]  where just because of the number of patients involved, even small mistakes can quite quickly
[02:48.760 --> 02:54.760]  be amplified into affecting large numbers of people. And we're all in this for patient care
[02:54.760 --> 02:59.720]  and people. So we do really want to make sure they're at the center of what we do. But we do
[02:59.720 --> 03:05.640]  see a need to scale the use of artificial intelligence and machine learning in the NHS.
[03:05.640 --> 03:09.480]  And really our manifesto is about the challenges in doing that scaling. So the last page of our
[03:09.560 --> 03:15.800]  manifesto is calls to actions, really around helping get the scalable adoption of these
[03:15.800 --> 03:21.960]  technologies into the NHS and get them into clinical and administrative workflow. And I
[03:21.960 --> 03:27.640]  guess we really had kind of three areas of those calls to action for the NHS and health leadership
[03:27.640 --> 03:33.560]  in the UK fall into. There's one about kind of avoiding duplication. Our members spend a lot of
[03:33.560 --> 03:39.000]  time doing the same thing multiple times, particularly in demonstrating compliance.
[03:39.800 --> 03:45.560]  We've really got a lot of funding coming through, but it's fairly short term. It's one or two year
[03:45.560 --> 03:50.520]  funding. Even people with technologies that have demonstrable benefits are having to go year on
[03:50.520 --> 03:56.920]  year back to funders to ask for money to renew the license or the software as a service costs.
[03:57.000 --> 04:03.800]  And also just around some of the barriers we encounter, lots of different questions,
[04:03.800 --> 04:09.640]  different templates, when really it would make sense to try and standardize at least 80% of what
[04:09.640 --> 04:15.720]  we do with the NHS so that we're not constantly answering the same questions in a slightly
[04:15.720 --> 04:21.640]  different way. Thanks Graham. And even sometimes contradictory questions in the same way.
[04:21.640 --> 04:28.280]  Absolutely. Very true, very true Ben. And Ben, I think obviously the work that we've got going
[04:28.280 --> 04:33.000]  on in the AI Special Focus Group, we've also got our Imaging IT Special Focus Group, which I know
[04:33.000 --> 04:37.640]  you're also a member of and have been for many years. And I know we have our joint meeting at
[04:37.640 --> 04:42.920]  UKIO each year. Why do you think it's important for the two groups to have that communication?
[04:44.200 --> 04:51.240]  Obviously a huge crossover between the two. Imaging IT, AI, AI is IT. The systems always
[04:51.240 --> 04:55.240]  have to talk to each other. And actually that cross-fertilization between those groups is
[04:55.240 --> 05:02.040]  really useful. I think there's lots of smaller new players in the AI space who maybe wouldn't
[05:02.040 --> 05:06.360]  have joined the imaging IT group because they've been traditionally the big PACS vendors, the
[05:06.360 --> 05:14.680]  Siemens, Philips, Agfa, GE, etc. So actually it's a really good introduction for those smaller
[05:14.680 --> 05:21.000]  companies into that environment, working with all the different parties that are there and
[05:21.000 --> 05:26.120]  sharing that knowledge and standardization. And hopefully they learn as much as we do from them
[05:26.120 --> 05:31.320]  as the bigger companies in their more agile ways of working. But they also have to understand the
[05:31.320 --> 05:37.880]  standardization and why we have this focus on trying to make sure we get rid of the duplication
[05:37.880 --> 05:44.840]  and all those things that, as Graham alluded to before. Yeah, absolutely. And we recently
[05:44.840 --> 05:50.360]  launched our imaging IT manifesto as well with a fantastic event at Bletchley Park. And when you
[05:50.360 --> 05:56.680]  look at the AI and imaging IT manifesto, whilst they're very focused on the individual areas,
[05:56.680 --> 06:03.560]  things around consistency, connectivity, innovation, upscaling are all the same across
[06:03.560 --> 06:08.760]  the different areas. So I totally agree that there needs to be that connectivity between the two
[06:08.760 --> 06:14.680]  groups as well. It'd be great to bring in the digital pathology team into that as well. It's
[06:14.680 --> 06:19.720]  all part of the same network, same environment. It's many of the same organizations working in
[06:19.720 --> 06:23.800]  all those spaces. There's AI in digital pathology, there's perhaps vendors in digital
[06:23.800 --> 06:29.560]  pathology. So all of us coming together is only beneficial for the customers, for the NHS,
[06:29.560 --> 06:35.720]  and for the patients at the end of the day. Absolutely. Yeah, I always find AI so interesting
[06:35.720 --> 06:40.840]  because you get such a mixed bag reaction. I know we do, and I'm sure you do even more so.
[06:41.400 --> 06:45.560]  As I say, you get those that are probably really excited. You've got those that are really concerned
[06:45.560 --> 06:51.240]  about what it means. So yeah, I think it's fascinating, really. But obviously looking
[06:51.240 --> 06:55.800]  ahead and horizon scanning, what is next for the Axrem AI Special Focus Group?
[06:56.520 --> 07:04.040]  Gosh, where to when next? I think having launched our manifesto in February, it's really up to the
[07:04.040 --> 07:10.040]  group and member companies to start executing on it. So first of all, that looks like carrying out
[07:10.040 --> 07:16.040]  some of the practices that we said we'll do. So helping to build the evidence base for artificial
[07:16.040 --> 07:20.360]  intelligence in real life clinical workflow, which I know a lot of our members are doing.
[07:20.360 --> 07:26.520]  It's great that bodies like NICE now come to us as an industry group to ask for representatives
[07:26.520 --> 07:31.240]  for consultation on things like early value assessments or EVAs. That's where NICE are
[07:31.240 --> 07:36.040]  trying to understand the evidence base for an emerging technology and try and see quite quickly
[07:36.680 --> 07:40.600]  what clinical benefits it might bring and understand what gaps there are in the evidence
[07:40.600 --> 07:46.040]  for holding it up from becoming a kind of widely adopted technology. So that's been really good.
[07:47.400 --> 07:52.440]  And just getting more and more involved with stakeholders, of which there are many,
[07:53.240 --> 07:57.480]  depending on what kind of AI technology you've got, you might well be needing to interact with
[07:57.480 --> 08:03.480]  NICE, the Care Quality Commission, their equivalents in the devolved nations as well,
[08:03.960 --> 08:10.200]  with the Medical Healthcare Regulated Products Agency, who are involved in our meetings as well,
[08:10.200 --> 08:14.120]  as well as professional bodies like the Royal College of Radiologists or the Society and
[08:14.120 --> 08:19.480]  College of Radiographers, which we also have great connections with and they join many of our
[08:19.480 --> 08:24.120]  externally focused meetings. So it's about continuing to build relationships with those
[08:24.120 --> 08:29.880]  and Sally and Melanie and the team have done great work over the last few years in getting us into
[08:29.880 --> 08:37.960]  people's minds when the topic of AI comes up so that they come to us and know that they can get
[08:38.680 --> 08:43.880]  useful point of view. And really just trying to, I think, remove some of those barriers that are
[08:43.880 --> 08:50.280]  holding us up, either by means of NHS, Department of Health, social care stakeholders, or even
[08:50.280 --> 08:54.920]  getting in front of parliamentarians who set legislation and who have a kind of pro
[08:55.480 --> 08:59.400]  innovation agenda. And again, some great work being done on that, which I think we can really
[08:59.400 --> 09:07.000]  build on throughout 2025 and into 26. So we just want to try and remove those barriers to upscaling
[09:07.000 --> 09:13.640]  and make sure that we're working with the whole community to try and get things moved forward.
[09:15.240 --> 09:18.840]  Only yesterday Graham and I were talking to Department of Health and Social Care
[09:18.840 --> 09:25.080]  about our favourite topics of DTAX and DPIAs and some of the documentation that we're all
[09:25.080 --> 09:30.360]  asked to fill in differently for every single NHS trust, different version etc and the lack
[09:30.360 --> 09:34.680]  of standardisation. And actually it was great to see during the presentation yesterday that
[09:34.680 --> 09:39.480]  it does look like they have been listening and that there will be a process coming on board in
[09:39.480 --> 09:47.160]  around 12 months time to help drive the adoption of solutions, AI solutions, IT solutions to make it
[09:47.160 --> 09:53.880]  far, far quicker. Yeah and that's a good point. We all want as responsible members to comply with
[09:53.880 --> 09:58.280]  all these things like data processing impact assessments and demonstrate that we're meeting
[09:58.280 --> 10:02.840]  all applicable standards so that hostiles deploying our technology can know that they'll work. So
[10:02.840 --> 10:08.360]  we're certainly not against the process itself and the reason behind it. It's more just the way it's
[10:08.360 --> 10:14.440]  being executed is really causing a productivity challenge, not just for suppliers having to
[10:14.440 --> 10:19.880]  recapitulate the same statements again and again, but also for the NHS. It really doesn't make sense
[10:19.880 --> 10:25.560]  for this technology to be assured and compliance checked at every single NHS trust when some of
[10:25.560 --> 10:31.080]  that could be done centrally. So I'm hoping that in the forthcoming reorganisation in the NHS in
[10:31.080 --> 10:35.480]  England there'll be some thought given as to how that can be achieved and there were some very
[10:35.480 --> 10:41.400]  positive noises from the Department of Health and Social Care at our recent imaging IT manifesto
[10:41.400 --> 10:46.040]  launch about doing exactly that. So I think I'm quite encouraged but we've still got quite a long
[10:46.040 --> 10:51.560]  way to go before we can really upscale the adoption of AI machine learning technologies in the NHS.
[10:52.360 --> 10:59.080]  And I think as well we see in our AI special focus group that a lot of the companies are SMEs
[10:59.080 --> 11:04.760]  so actually adding complexity to the system and a lot of duplication for an SME
[11:05.880 --> 11:11.480]  it makes the job much harder and ultimately all that is doing is adding cost into supply chain
[11:11.480 --> 11:18.920]  because it's taking you guys a lot longer having to on multiple occasions complete the same
[11:18.920 --> 11:24.760]  documentation. So like Graham alludes to you know at the point of procurement you often have
[11:24.760 --> 11:31.240]  done all of this and it should be shared across the system so that you guys aren't having to
[11:31.240 --> 11:36.840]  add extra workload. We've touched on there around upscaling and I know that this is one of the
[11:36.840 --> 11:41.720]  biggest topics and it's not just talked about in AXREM it's talked about by the societies
[11:41.720 --> 11:48.360]  and royal colleges also working in our space and I know that upscaling now is really important.
[11:48.360 --> 11:55.720]  I think we saw that 21 million of funding that has hopefully shown some really good case studies
[11:55.720 --> 12:04.200]  of how AI can be used efficiently and we now need to try and adopt that on a much larger scale so
[12:04.200 --> 12:10.760]  that patients get the very quickest and best diagnosis. So why do you guys think it's important
[12:10.760 --> 12:16.920]  that the NHS upscales and what difference would this make to patient care? We definitely have a
[12:16.920 --> 12:23.080]  capacity challenge in terms of the number of professionals and carers available. The royal
[12:23.080 --> 12:28.600]  college not just in radiology but also in pathology have highlighted in both their reports
[12:28.680 --> 12:35.640]  recently they do workforce census. We are just facing an ever growing shortage of trained
[12:35.640 --> 12:40.040]  clinicians. There haven't been enough training places made available over a number of years
[12:40.040 --> 12:45.560]  and the number of radiologists needed for example I think is you know running into the thousands now
[12:45.560 --> 12:50.840]  and will only get larger as work increases and I think that's partly because of two reasons. One
[12:50.840 --> 12:56.920]  is just the volume of imaging work increases year on year. Things like chest x-ray are fairly stable
[12:56.920 --> 13:01.880]  and growing at two to three percent a year but the multi-slice modalities grow anywhere between
[13:01.880 --> 13:08.360]  eight and fifteen percent a year in terms of number of exams done within England and Wales
[13:08.360 --> 13:12.920]  and not just that the sheer amount of data involved in each of those exams is increasing
[13:12.920 --> 13:18.920]  all the time as well. When I first started in radiology a CT brain scan was done on five
[13:18.920 --> 13:24.440]  millimeter slices so that meant that would be usually about 40 to 45 images to review.
[13:24.440 --> 13:28.760]  Now there are 400 and we do it at half millimeters and some of our members latest
[13:28.760 --> 13:34.360]  scanners are able to go down to the kind of 0.2 millimeter so you can easily imagine that soon
[13:34.360 --> 13:39.560]  will be a thousand images per brain scan and that's great that allows us a lot more diagnostic
[13:39.560 --> 13:45.320]  accuracy but it also means there's just a lot more to look through with a concern about missing stuff
[13:45.320 --> 13:50.360]  and you know not not catching everything that you should be seeing in a scan and I think that's
[13:50.360 --> 13:55.400]  really where our members technology can help in the image analysis space is by acting as a safety
[13:55.400 --> 14:00.760]  net and helping with the whole kind of getting it right first time agenda or girth agenda so that
[14:00.760 --> 14:06.680]  patients get the the right care at the at the first time of presentation and not later on.
[14:06.680 --> 14:13.240]  Ben you got anything to add to that? We shouldn't forget that actually AI has been around in
[14:13.240 --> 14:18.440]  in the medical imaging space not not just for two or three years we've been doing this for 15
[14:18.440 --> 14:23.320]  sometimes 20 years so whilst we didn't necessarily call things AI historically
[14:24.440 --> 14:29.160]  it would they were just algorithms that did computer aided diagnosis can as it used to be
[14:29.160 --> 14:35.320]  called it's all the same stuff you know so it's not actually as new technology as it sounds like
[14:35.320 --> 14:40.040]  it is sometimes you know it's always promoted as what AI is coming we've been using it for years
[14:40.040 --> 14:44.040]  clinicians have been using it for years but actually that they need to make better use and
[14:44.040 --> 14:48.680]  more use of it and when there are tools which can be made quicker and simpler they just need
[14:48.680 --> 14:54.040]  to be adopted because as Graham says there simply isn't the number of trained radiologists all
[14:54.040 --> 14:59.240]  radiographers reporting radiographers to cope with the the workload we can't outsource everything
[14:59.240 --> 15:03.400]  because we're outsourcing to the same people it's clinicians who are working more in their
[15:03.400 --> 15:08.760]  private time to to earn more money but it's the same people and there's only so many of them
[15:08.760 --> 15:13.000]  and they are an aging breed unfortunately there's not been so many coming in at the lower end
[15:13.720 --> 15:21.000]  and anything we can do to to upskill those people quicker or to to level out the playing field so
[15:21.000 --> 15:26.440]  that a less trained or newer radiologist can be meeting a similar standard to the those very
[15:26.440 --> 15:30.920]  very experienced ones that are retiring the better the other better for the patient at the end of
[15:30.920 --> 15:36.360]  the day I think you've both made some really useful points there and I think there's a few
[15:36.360 --> 15:42.920]  that AI plays into the workforce crisis by creating some efficiencies which will help
[15:42.920 --> 15:50.680]  clinicians in terms of radiology AI is far more advanced I would say than any other health care
[15:51.240 --> 15:58.760]  sector and I believe the figures are something like 75% of AI in health care is in radiology
[15:58.760 --> 16:03.720]  and we've even seen that recently when we had our first digital pathology special focus group and
[16:03.720 --> 16:08.280]  they were talking about AI and they were saying there's obviously a lot of lessons that can be
[16:08.280 --> 16:15.000]  learned from radiology so I do feel that we're you know advanced we want to make sure it's safe
[16:15.000 --> 16:20.840]  for patients but equally I think at some point we've got to take that leap forward and adopt at
[16:20.840 --> 16:27.400]  scale to ensure that patients get like I say before the very best care and I think the other
[16:27.400 --> 16:31.320]  thing we've got to remember is the the patients and the waiting lists at the moment are just
[16:31.320 --> 16:37.240]  so high when I first came into the NHS it was off the back of a wave of NHS investment from
[16:37.240 --> 16:42.600]  the the last Labour government under Tony Blair and then later Gordon Brown and waiting lists you
[16:42.600 --> 16:48.280]  know specific initiatives were done to get them right down and people were talking about the 26
[16:48.280 --> 16:53.960]  week you know target now we're talking about a 52 week target and although the waiting lists have
[16:53.960 --> 17:00.040]  been chipped away since the pandemic they are just not falling at the rate anybody would wish
[17:00.040 --> 17:06.120]  so we do need to look at you know making sure the system is working as efficiently as possible with
[17:06.120 --> 17:10.440]  all the resources that are available and that will look like AI that doesn't go anywhere near
[17:10.440 --> 17:16.440]  assessing x-rays and pictures as well so for back office functions there's some great work
[17:16.440 --> 17:22.600]  from our members around trying to predict which patients might not turn up and then use that to
[17:22.600 --> 17:27.960]  do targeted interventions so that we can kind of call them or text them or encourage them to turn
[17:27.960 --> 17:33.400]  up for their scan because a scan slot is a very precious resource and also being able to potentially
[17:33.400 --> 17:38.680]  overbook in order to make sure that all the scan time that is there is is correctly used and kind
[17:38.680 --> 17:43.800]  of taking account of who might not turn up or have to postpone till later so there's lots of other
[17:43.800 --> 17:48.920]  opportunities as well as our members beginning to get into the area of large language models
[17:48.920 --> 17:55.720]  to help with reporting and transcription which is just an area already in active use for clinical
[17:55.720 --> 18:00.200]  noting in a lot of places and we're just going to see more and more of that across the health and
[18:00.200 --> 18:04.920]  care system as well so it's important although the pictures are the headline grabbing bits there's
[18:04.920 --> 18:09.960]  a lot more to radiology and radiotherapy AI than just analyzing scans and x-rays
[18:11.640 --> 18:15.560]  yeah and it's important like you say that we do recognize that as well as I say we're all
[18:15.560 --> 18:19.880]  patients at the end of day and we all want we all want everything to be as safe as possible but then
[18:20.520 --> 18:27.240]  we do want to get seen so it is finding that balance isn't it but um yeah no thank you
[18:27.240 --> 18:31.960]  so obviously moving on slightly so what do you think are the benefits of being involved
[18:31.960 --> 18:39.560]  in the ai special focus group and axrem as a whole that's a great question I was just
[18:39.560 --> 18:44.600]  thinking hard about some of these as I met somebody the other day who isn't a member
[18:44.600 --> 18:48.600]  but was interested in what action we're doing and wanted to know a bit more so that really caused
[18:48.600 --> 18:53.960]  me to reflect on the benefits that we got in our company when we first joined and are still getting
[18:53.960 --> 19:00.680]  now as members so I would characterize that as as you said earlier sally a lot of the companies are
[19:00.680 --> 19:05.480]  small and medium enterprises and frankly even the ones that are large multinational corporates when
[19:05.480 --> 19:09.480]  I worked for one in the kind of AI imaging division there was still only a few of us so
[19:10.280 --> 19:15.640]  the workload of kind of stakeholders and consultations coming our way and guidance that
[19:15.640 --> 19:20.600]  needed assessed we couldn't do it all on our own and that's where we can kind of share out some of
[19:20.600 --> 19:25.880]  that some of that workload amongst the membership we've got some great people who help axrem respond
[19:25.880 --> 19:32.760]  to consultations and who help on kind of standards work so and none of that really is possible for
[19:32.760 --> 19:37.800]  any one company to to do alone so there's the the benefit of that you get access to those
[19:37.800 --> 19:43.240]  stakeholders as well in a way that's actually quite difficult for a company to achieve on their own
[19:43.960 --> 19:51.240]  and also the kind of the the pooled expertise of our special focus group always just amazes me
[19:51.240 --> 19:56.600]  how much we can all learn from each other and our previous experiences and roles that we've had in
[19:56.600 --> 20:01.560]  the past so that those those are kind of three of the benefits whether you're a small or large
[20:01.560 --> 20:06.440]  company and I think we then talked about kind of interoperability right at the beginning and
[20:06.440 --> 20:13.000]  connecting to other systems none of our solutions really will work entirely in isolation from the
[20:13.000 --> 20:18.200]  rest of the IT environment in a hospital so the fact that you've got the the imaging IT group with
[20:18.200 --> 20:23.880]  its members who are doing packs and radiology information systems and reporting solutions
[20:24.600 --> 20:28.920]  it's a great opportunity to to network with them in person so that we can
[20:28.920 --> 20:35.240]  network our systems to each other so that that's a real benefit too because together we can deliver
[20:35.240 --> 20:40.920]  the can deliver the real value into the care pathway by by integrating our solutions into
[20:40.920 --> 20:42.680]  clinical and administrative workflow
[20:45.560 --> 20:52.280]  if you look at our joint meeting at UKIO there's probably between 700 and a thousand years worth
[20:52.280 --> 20:57.720]  of experience in the marketplace in at that meeting that that level of knowledge and experience
[20:58.280 --> 21:02.920]  can only be beneficial to all of us you know that there are challenges I may face or graham
[21:02.920 --> 21:07.160]  may face or anybody may face that somebody else will have seen at some point or we're facing the
[21:07.160 --> 21:13.160]  same challenge so we can then get a a combined response you know again the DPA is our classic
[21:13.160 --> 21:19.000]  example at the moment where any one company's been fighting for this for several years and
[21:19.000 --> 21:25.080]  getting nowhere but actually as a body as a whole industry we do get some progress and then a lot
[21:25.080 --> 21:29.880]  of that is down to the work that that Sally and Mel and team do as well in parliament and engaging
[21:29.880 --> 21:34.920]  with the the parliamentarians that the decision makers higher up as well on the behalf of everybody
[21:34.920 --> 21:39.080]  and we all benefit from that most notably at the end of the day the patient
[21:40.520 --> 21:43.800]  that's that's a great point ben about the coupled experience i think we should do a
[21:43.800 --> 21:48.120]  slido poll at our next joint meeting in june to find out exactly how many years it is
[21:48.120 --> 21:52.040]  if people are willing to divulge that information it's given me a great idea
[21:53.160 --> 21:58.600]  we should definitely include that and i would say as the ceo of AXREM our strength is the
[21:58.600 --> 22:05.800]  expertise within membership i'm here to facilitate and you know make sure things happen but the
[22:05.800 --> 22:11.800]  expertise really is within the membership and i also think strengthening numbers we've got nearly
[22:11.800 --> 22:17.560]  80 member companies that we represent now together as one we are much stronger like you say than
[22:17.560 --> 22:25.000]  individual companies trying to lobby or bring about change i also think that the networking
[22:25.080 --> 22:30.520]  opportunities that we offer members especially have seen that in the ai space where we have
[22:30.520 --> 22:36.360]  member companies that join and then i see partnerships emerging with some of the oems
[22:36.360 --> 22:41.640]  and other members and i think that that has been created by building those relationships within
[22:41.640 --> 22:49.160]  AXREM and i think as we know we kind of have this we want to be the industry voice and i definitely
[22:49.160 --> 22:55.240]  think that we've really improved our we've elevated our position and we've become a lot
[22:55.240 --> 23:01.400]  more visible and i think that you know if there is a pinch point or challenge or something government
[23:01.400 --> 23:07.880]  or you know one of the different organizations wants to speak about they do often now approach
[23:07.880 --> 23:13.000]  AXREM and and we're able to give them that industry voice you know rather than having
[23:13.000 --> 23:17.960]  to reach out to lots of individual companies so totally agree with all your points but obviously
[23:17.960 --> 23:24.760]  i am a bit biased but that's great you're allowed to be biased sally it's fine
[23:26.040 --> 23:30.520]  right so moving on um and i'm quite interested actually to see what your responses are to this
[23:30.520 --> 23:36.360]  because obviously you're the ai special focus group so quite futuristic etc so if you had a
[23:36.360 --> 23:43.080]  time machine would you go to the future or would you go back in time and why no it wants to go
[23:43.160 --> 23:49.320]  fast graham well i guess you're asking me do i want to go forward to the year 3000 and see if
[23:49.320 --> 23:56.120]  we really do live underwater but i've got to say i would want to go back to the past i think as
[23:56.120 --> 24:01.400]  strangely as it might seem rather than see the future i did think about which period of the past
[24:01.400 --> 24:06.360]  our recent visit to bletchley park made me think that would be an amazing place to visit i
[24:06.360 --> 24:10.920]  definitely wouldn't have been breaking codes that is not my 40 at all i'd probably just have been
[24:10.920 --> 24:14.760]  shoving paper around on a trolley because that would be about the sum total of my contribution
[24:14.760 --> 24:20.600]  but i think i've settled on i would love to go back to bible times just to actually hear and
[24:20.600 --> 24:24.840]  see the teachings of jesus that would be really interesting to me i'd have loads of questions
[24:24.840 --> 24:29.480]  i'm not sure i'd like the answers if i if i got to ask one but i just think that'd be amazing i'd
[24:29.480 --> 24:34.440]  have to learn biblical aramaic as well so that might be quite difficult but that i think would
[24:34.440 --> 24:39.560]  be the the most amazing thing so you like to challenge yourself as well at the same time
[24:40.840 --> 24:46.440]  excellent ben contrary to graham i'm i'm a mathematician at heart that's what i did
[24:46.440 --> 24:52.520]  my degree in and puzzles and codes and something i love to do i have several bletchley park challenge
[24:52.520 --> 24:58.280]  books set here um challenge now of course is that everything gets so much more complicated i could
[24:58.280 --> 25:02.280]  cope with the things they did then i can cope with the bletchley park puzzles not sure i can
[25:02.280 --> 25:06.280]  cope with some of the ones that are that are coming up in the future so that there's so much
[25:06.280 --> 25:11.960]  that's happened in the past that i would love to see but actually the end of the day that there's
[25:11.960 --> 25:16.280]  so much so many challenges going on in the world at the moment i would quite like to just jump
[25:16.280 --> 25:21.160]  forward 20 years past the mess that's going on in various places at the moment and see how it all
[25:21.160 --> 25:30.520]  turns out and hope that it turns out for the best yep absolutely that's interesting graham wants to
[25:30.520 --> 25:36.280]  go back you will go forward excellent thanks and that is very interesting answers especially like
[25:36.280 --> 25:42.840]  we say from our futuristic ai uh special focus group convener advice convener so today i think
[25:42.840 --> 25:48.520]  we found out a lot more about graham and ben and some of further insights into AXREM's ai special
[25:48.520 --> 25:53.480]  focus group so i'd love to say a big thank you to graham and ben for joining us and thank you to all
[25:53.480 --> 25:58.920]  of our listeners join sally and i again next week when we will be speaking to nicola fishwick about
[25:58.920 --> 26:04.520]  the axrem ultrasound special focus group if you have enjoyed today's podcast don't forget to hit
[26:04.520 --> 26:10.440]  subscribe or feel free to share the podcast with friends
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