{"id":9723,"date":"2025-09-02T07:14:08","date_gmt":"2025-09-02T07:14:08","guid":{"rendered":"https:\/\/weareoakland.com\/?p=9723"},"modified":"2025-09-02T07:14:10","modified_gmt":"2025-09-02T07:14:10","slug":"generative-ai-project-success","status":"publish","type":"post","link":"https:\/\/weareoakland.com\/blog\/generative-ai-project-success\/","title":{"rendered":"Generative AI: How to Make Your Project a Success"},"content":{"rendered":"\n

MIT\u2019s recently published report<\/span><\/a> concludes by stating that in 2025, \u201895% of generative AI pilots at companies are failing\u2019 – and it doesn\u2019t surprise me one bit. Thousands of AI proof of concepts are being made under the guise of massive easy cost savings and robot magic simply finding all the answers – but many are doomed to fail. We\u2019ve seen the amount of \u2018gotchas!\u2019 and obstacles first-hand and it\u2019s all too easy to fall into traps and end up with something which is just quite \u2018meh\u2019.<\/p>\n\n\n\n

So, how do you make sure your generative AI project actually brings value and still exists 12 months later? I\u2019ve written out some learnings from our experience scoping, building and deploying AI solutions at Oakland Everything Data<\/span><\/a>. (I then ran this blog through CoPilot to make sure it read okay, but I decided to ignore a lot of the suggestions. I secretly worry all content on the internet will sound the same in a few years, but Nicola, our Marketing Manager, assures me it won\u2019t\u2026)<\/p>\n\n\n\n

What is Generative AI?<\/h2>\n\n\n\n

Generative AI is an artificial intelligence<\/span><\/a> that creates original, new content. Think text, images, videos, music. It learns from huge datasets of information that already exist, spotting patterns and structures in the data to then produce novel outputs. When using a GenAI model, users give it a prompt. It then creates the original content off the back of that – ChatGPT is the most well-known example and one you\u2019ve probably already used.<\/p>\n\n\n\n

Solve the Right Problem with the Right Tool<\/h2>\n\n\n\n

So, how should businesses choose the right use-case to solve with AI? <\/p>\n\n\n\n

Firstly, think about what you\u2019re trying to do and consider if you even need <\/em>AI. Hype is powerful and budgets often get approved on buzzwords, like GenAI. But, spending money on a tool which will make a \u2018pretty interesting\u2019 case study<\/span><\/a> and nothing else won\u2019t lead to a successful, money saving solution. <\/p>\n\n\n\n

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Practical AI for business<\/span><\/a><\/div>\n<\/div>\n\n\n\n

At Oakland, we often run workshops with clients to discuss where and how they could use AI in their business. The shortlist usually ends up at around 10 or 20 project candidates. More often than not, 80% of these problems are just general or more advanced analytics<\/span><\/a> problems, with some golden AI problems buried amongst them. This isn\u2019t an issue as they could be brilliant candidates in their own right – maybe even solvable using some element of AI to enhance the\u00a0 output. But getting the right problem to solve is important.<\/p>\n\n\n\n

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\u201cChoose a challenge which will have a high impact on something lower risk. Avoid regulated areas, critical workflows, or things which require more exact output. Look for problems which are time consuming, automatable, and areas where AI can add to existing human processes, rather than fully replacing them.\u201d<\/strong><\/p>\n\n\n\n

Jack Evans, Principal Consultant<\/p>\n<\/blockquote>\n\n\n\n

Making work easier so individuals can achieve more or be more impactive is the key, as is choosing an existing process to improve rather than creating something completely new.<\/p>\n\n\n\n

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Readiness of UK business for GenAI<\/span><\/a><\/div>\n<\/div>\n\n\n\n

AI Solutions can be More than Chatbots<\/h2>\n\n\n\n

There\u2019s nothing wrong with a good chatbot. In fact, they\u2019re often an ideal way for a user to interact with an AI model. The problem is that people often think this is the best and only way to use AI within an organisation, because it\u2019s the most visible format for LLMs. But they\u2019re not the only way! <\/p>\n\n\n\n

AI can come in many different forms. The best solutions use the best parts of different tech to solve a problem and have a bigger impact. Examples include:<\/p>\n\n\n\n