Still learning
Back at the start of August, I attended the MCC Summit on AI
and Marketing, a two-day virtual course. While I am already completing an
apprenticeship in Business Impact with AI, I am also interested in exploring a
different perspective; how it can be used in fundraising.
I worked in marketing for many years even before becoming a
fundraiser. I was using email in the 80s (when we had large green screens and 8”
floppy disks), and I remember the launch of marketing automation in the early
90s (our floppy disks were now a lot smaller and less flexible). AI has been
here a long time, it’s just not been as visible as it is now.
I wanted to learn about the opportunities, challenges and
potential risks associated with AI and how it’s being applied now, particularly
how it might apply to my role and the organisations I work for. The AI
Apprenticeship covers some great stuff, but I needed to learn more about the
fundraising/marketing context.
My motivation for taking the course (and paying for it myself)
was simple: I want to contribute as much as possible to the charities I work
for. And, of course, I want to develop myself so that I have the skills I need
to keep working (which I am planning to do beyond my official state retirement
age*).
Combining business analysis skills with a deeper
understanding of AI and marketing gives me stronger tools for strategic
thinking. It also helps me support my team as they develop their own confidence
and capability in using AI appropriately and effectively. I found one of the best
ways of embedding your learning is to share – you quickly find out what you
haven’t quite got right when colleagues ask you questions.
Working within the mental health sector means I'm
particularly conscious of safeguarding concerns around AI. Publicly accessible
tools such as ChatGPT, Claude and Grok are evolving rapidly, and there are
valid questions around ethics, safety and oversight. In some ways, it reminds
me of the conversations the world is having about the impact of social media
and the unintended consequences that can emerge when technology develops faster
than regulation (which is infrequently speedy).
We've already seen examples of people using AI as a sounding
board for personal issues, sometimes with tragic outcomes when AI chats have
reinforced false information and unhealthy behaviours. That’s one of the reasons
why charities like ours are rightly taking a cautious and considered approach
to AI adoption. But they are supporting me and several other colleagues on the
AI Apprenticeship, so I think we are progressive compared to many
organisations.
I believe AI is going to come under greater scrutiny, even
though the UK has not adopted the tighter EU’s legislation on this (but there
are some great guidelines you can find on the .gov.uk
website). The dangers of AI make headlines regularly (eg the Open AI hacking of
Hugging Face). Something to do with the delights in doomscrolling or, as in the
case of a sceptical article from the
Guardian, maybe it’s about grabbing headlines to attract investors? Either
way, we are going to need more guardrails and (pun intended) guardians.
At the same time, we cannot ignore the benefits. For me,
AI's greatest value lies less in creating content (your fundraising appeals won’t
be AI generated, I promise) and more in supporting decision-making. AI can do
what my brain can’t do quickly - it can help analyse large datasets, identify
trends, surface anomalies and flag areas that require closer human
investigation. Used well, it can help us work more effectively without
replacing the critical judgement that only humans can provide. It is certainly
doing that for me.
My Biggest Takeaway is using AI as a Thinking Partner
The most valuable lesson so far is possibly learning how to
use AI as a thinking partner.
There is ongoing debate about whether AI will make people
less capable thinkers. My experience has been quite the opposite. Used
thoughtfully, and crafting prompts properly, AI can challenge assumptions,
strengthen analysis and inform and improve decision-making.
For example, I’d done a review that sounded very much like
my point of view (culminating my experience of course), but also sounded
defensive. I created a prompt that asked AI to act as the audience I would be
presenting to and critique my work from that perspective. The questions it
generated were insightful and challenging, helping me strengthen my review
before sharing it. It helped me deliver a better review because it gave me an
unbiased, neutral critique.
I also experimented with more complex prompts designed to
facilitate structured conversations around strategic issues. By working through
a series of questions and responses, AI helped me clarify ideas and test my
thinking in ways that I found genuinely useful.
The final outputs of work I’ve developed using AI remain
firmly rooted in my own knowledge and experience and analysis of evidential
data. If I had to quantify it, I would say the result was approximately 75%
human expertise and 25% AI-supported insight.
However, AI helped shape and refine my thinking, challenge
assumptions and benchmark ideas against external information. It speedily
analysed historical data, reviewed sector reports and gave me additional
insight that would have taken me a lot of reading to reach on my own.
Ultimately, AI has helped me do my job better. It has made
me more productive, helped me think more strategically and enabled me to use my
time more effectively, even while balancing work with continued study.
Advice for Anyone Interested in learning about AI
My advice would be to start by thinking about what you want
AI to help you achieve.
Rather than choosing a generic AI course, look for learning
opportunities that align with your role, responsibilities and objectives. The
most valuable training is often the kind that allows you to apply what you've
learned immediately.
Equally important is choosing learning providers and
resources that you trust. AI is developing rapidly, so focusing on practical
skills and real-world applications can be far more beneficial than trying to
learn everything at once.
And though I encourage experimentation, learning the basics of
prompting will save you a lot of time and effort, and reduce your
experience of, what we call in the music industry, ‘Loud, confident, and wrong’.
Looking Ahead
One of the most common concerns people have about AI is
whether it will eventually replace jobs. My view is that, regardless of how you
feel about AI, understanding its role in the future workplace is going to be
important. I told my 15 year old granddaughter that she needed to understand AI
because there is every likelihood that she will need to use it when she joins
the workforce. You do not need to become an AI specialist, but you do need to
understand how these tools can support and enhance the work you do.
A quote from AI researcher Oren Etzioni captures this
perfectly:
"You won't be replaced by AI. You might be replaced by
a person who uses AI better than you."
Remember that. The
opportunity lies not in competing with AI, but in learning how to work with it using
it responsibly, thoughtfully, effectively and ethically.
* August 2027 – eeek!!
AI transparency: This is not AI slop, it is Carolyn slop, tidied by AI. The image is created by ChatGPT after I prompted it asking how it would illustrate this article.
Useful links
- Putting people first at Rethink and MHUK
- Open AI article on The Guardian
- Coursera - a resource for online learning for lots of things, including AI
Liked this? Try...
- New life (AI and music)
- Mentoring
- Working in the 80s - from my start in blogging 20 years ago
