Artificial Intelligence is a huge spectrum that covers a wide range in terms of cost and complexity. In this article, we break down how you can secure a return on your technology investment with AI and even prove the need for it before you begin app development.
The buzz around Artificial Intelligence has been loud and constant since OpenAI made ChatGPT freely accessible to the public at the tail end of 2022. After decades of hype and what-ifs, it took an easy-to-use user interface backed by a powerful learning language model. With that, AI lept from being emerging tech to a day-to-day tool for consumers and businesses alike.
22% of people already regularly use AI tools in their work. 79% have been exposed to it. In the same way that collaborative software changed how people worked and interacted with one another, AI will mark a fundamental shift in how we work. Even if all the business cases aren’t clear yet, the opportunities and benefits are.
AI, however, is a huge spectrum. It can cover chatbots, off-the-shelf GPT wrappers, and fully-fledged custom models. Because of this, the cost and complexity of integrating AI into your business can range from a £10 monthly subscription to hundreds of thousands of pounds.
With so many different options, it’s hard to know where you should start with artificial intelligence. Before you begin, you have to consider where you are now and what it is you want to achieve with the technology.
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The Starting Point
As a starting point, you need to ask yourself four key questions:
- Do you have the data you need in the right quantity and format?
- Do you know the requirements?
- Do you have the right skill sets and expertise to hand?
- Do you have the right business case?
In this section, we will explore how to make sure you can confidently answer yes to each one.
To get any kind of real value out of AI, you need a large amount of data and you need it in the right format. Implementing a deep learning AI model into a low-data solution will not produce the right results for your business or your users. Your data must be accurate and complete if you want to successfully integrate it into your solution.
There’s a proven correlation between the return on technology investment for AI and how modern the data behind it is. The better the classification and verification of your data, the more context your AI solution will have. The more context, the better it will be able to understand your business and add value.
Ethics, Security and Legal Considerations
As Microsoft once found out to its great embarrassment, bad data and training create bad AI. Understanding the ethics, security and legal considerations of AI is non-negotiable. Without that understanding, you run the risk of having your app exploited or falling foul of data protection laws. It’s how one person almost snagged themselves a $76k Chevy for $1.
AI needs humans in the loop with a sound understanding of how the technology works and what to consider to avoid unexpected exploits or errors. The data and the models powered by it need safeguarding and monitoring to keep them compliant and secure.
Skill Sets & Expertise
The ROI you get from AI will depend more on the people who implement and use it than it does on the underlying technology itself. It’s been proven that leaders in AI spend twice as much on the people, partners, and processes to handle the AI as beginners who often put all their budget into the tech.
To get started, it helps to have a trusted partner like Sonin support you with the ethical, security, and legal considerations. We understand how to implement new technologies successfully. We have more than a decade of experience helping clients across a range of different industries build digital products that deliver the right results.
Finally, for any AI project to succeed you need a clear business case. Like with any new technology, you have to understand the outcomes you want to achieve first. Only then will you be able to work out what the right solution looks like.
By defining clear objectives and desired results upfront, you can align your AI initiatives with strategic goals. This way, your investment will have a meaningful impact and real benefits across different levels of your organisation.
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Building the Business Case for AI
There are many different types of AI – they serve different purposes and provide different benefits. They can range from purely reactive with no memory to fully self-aware and human-like. They can be internal or external. In this section, we explore some of the most common AI use cases that offer a clear return on your investment.
Consumer AI Use Cases
The standard for what constitutes excellent customer experience is changing.
For a long time, we’ve heard about the importance of personalisation and convenience in improving the customer journey and increasing revenue. Before, these examples were often unrealistic unless you had a significant budget. But now there are tangible ways to deliver a superior customer experience with higher satisfaction and conversion rates.
- Conversational Interfaces: than chatbots, AI is able to add authentic and helpful conversational interfaces on existing platforms. This helps people interact with your business in a way that feels far more natural and find what they need with far less friction.
- Recommendation Engines: Rather than relying on “if-then” or “category-like” recommendations, AI offers the opportunity to present users with far more relevant and tailored suggestions – whether it’s in-app content, products, or more.
- Data Enrichment: With the right contextual UX, AI can enrich data to add extra value and insights. For example, activity logs in fitness apps can capture conditions automatically and compare results with huge data banks immediately to provide personalised insights and recommendations.
- Predictive UX Design: We’re already seeing better predictive and proactive UX in many of the tools users interact with on a day-to-day basis. Google Calendar meeting invitations proactively suggest agendas and relevant documents. The more users see this, the more they’ll expect it across all the apps you use. You’re competing with these tools whether you know it or not.
Good user experience design helps users do what they’re trying to do. Great user experience understands what users are trying to achieve and uses that to help them achieve it faster and more efficiently. As AI continues to creep into the tools your users engage with every day, “great” will become the new floor for their expectations.
Talk to one of our UX experts about how AI can help you create a consumer app that delights users and drives revenue.
Business Process Use Cases
AI also offers many benefits to your business. You can use it to give employees the tools they need to deliver the right results for your business rather than the low-value, repetitive tasks that can take up their time.
- Personal Assistants: AI-powered assistants can offer individuals in your company tailored insights, suggestions, and support. They can succinctly summarise documents, meeting notes, and more to pull out key insights and action items – making it easier for your team to focus on the work that matters.
- Media Generation: More and more, we will see automatic text, image, and video generation both in internal documents and in customer-facing content. Generative AI will free your employees up to focus on curating and refining rather than creating.
- Quality Control: AI can be a valuable reviewer by sense-checking important documents for simple mistakes while also offering suggestions for improvements that are tailored to the jobs at hand and their desired outcomes.
- Organisation and Classification: One of the biggest opportunities presented by AI is the automatic organisation and classification of your media and documents. Find out how we helped recruitment group Nursdoc to reduce the steps in its timesheet processing by 67%.
In an increasingly competitive landscape, these use cases can boost productivity within your workforce and increase revenue while freeing up your employees to innovate and add even more value.
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The AI Strategic Continuum
The AI strategic continuum is wide and vast. There will be quick wins where plugging an out-of-the-box AI tool or API transforms a spreadsheet of contact info into an interactive assistant that’s an expert in your customer base. There will also be large-scale digital transformation projects that take much more effort but provide a much larger return over a longer period of time.
Ultimately, the ROI you get on AI will be influenced by how AI-ready your organisation is. Having a trusted partner like Sonin App Development can help you strike the right balance between the quick wins and the long-term initiatives that will deliver long-term ROI.
To kick off a consultation on what AI can do for your digital products, get in touch with us today.