Previously available exclusively to tech giants, artificial intelligence is now making its way into more organizations’ processes. Now democratized, the technology can be used by all businesses to modify customer experiences, meet the changing needs of the market, soothe the pains of employees relying on guesswork – bring real value.
It does. Full Artificial Intelligence adoption can take years and eat up whatever there is in your budget. It’s an R&D project, and as such it has both the potential and risks. Studies show that many AI projects fall short of expectations and never deliver the value that was promised – it’s the problem of as many as 8 out of 10 AI implementations!
It all sounds scary, we’re aware of that. There’s this pixie dust (in other words: Artificial Intelligence) that can solve your business problems, but so far, getting hold of it feels nearly impossible. Unknown timeframe, unknown budget, unknown results. How’s that for working with data, when all is unknown?
It’s not all that dark, though. So why don’t we take a small step first, and make AI a strategic move, and not a leap of faith?
It can, and it should.
What if we told you that it is possible to check whether your AI will pay off? And do so without wasting months or spending hundreds of thousands of dollars. There is no point in developing something that won’t work. So before you commit, let’s challenge the idea of Artificial Intelligence being your problem solver.
In less than one month, we validated the idea of using AI to improve sales rates in a British telecom company – with over 91% success probability!
After full rollout of the AI-based system, our client ended up with more than 10x return on their investment.
An AI-based platform recommends the right courses to support employees’ development at one of the world’s biggest financial institutions.
The AI Sprint is a short-term, fixed process where we help you discover the potential for Artificial Intelligence in your organization, identify the most promising use cases, build the base for your data strategy, test and assess the solutions to show you what they’re worth.
First things first: we start with a talk. It is crucial to communicate well in AI projects, at every step of the way. It’s crucial from the very beginning to make sure everyone has a full understanding of the business, the pains, the hopes, and the assumptions.
Knowing your operations and your struggles, we can list Artificial Intelligence solutions that have the best chances to bring you quick wins and open up the path to company-wide AI adoption. We find the right algorithm for you looking at your objectives, requirements, and data.
The data science team performs the AI research – exploratory data analysis (EDA) – to discover patterns, spot anomalies, and test hypotheses. With the results, we have a full picture of what the data represents and how it can be used in the most efficient way.
There’s the moment of truth. We test various machine learning algorithms to find the best fit. We assess the probability of successful implementation of the selected solution, and we get you ready for the next steps with tailored recommendations for your AI journey.
Convince your stakeholders that Artificial Intelligence is worth the shot with the findings and results of the AI Sprint.
Organize relevant elements of AI adoption and standardize the way your company will work with AI projects.
See how to move forward strategically to make the most of AI adoption.
Get evidence that Artificial Intelligence can (or cannot) deliver tangible value to your organization.
We were really hyped up with the workshops and the method. We appreciate the input of the AI team and the involvement of the team leader, which made us feel taken seriously. It was very valuable. The way of working in data projects is not obvious, but Neoteric helped us choose the right method.
The PoC has shown you whether the idea is viable but also gave you a taste of what it’s like to work with external data scientists. The base of your data strategy and recommendations lay the groundwork for a successful, strategic implementation.
Now it’s time to bring the idea to life.
Your AI Sprint has tested a variety of models that can solve your problem, and at the end, you see which AI-based solution performs best. No matter if it’s a recommender system to suggest your customers the next purchase, predictive models to assess the risk of churn, dynamic pricing to increase your margin profit, speech recognition to improve customer service, or some other solution utilizing machine learning, we have a process that will help you bring it to life.
Gain valuable insights about future events and use Artificial Intelligence to predict e.g. customer churn or employee turnover to be more proactive.
Give your customers personalized, AI-based recommendations of products or content to boost their engagement, improve customer service, and increase sales.
Adjust your prices when needed – automatically. Dynamic pricing allows for a higher margin and better conversion rates.
Assess the value of items using AI, evaluate the probability of conversion (lead scoring) or verify credit risk (credit scoring).
Handle customer queries more efficiently with the help of NLP-powered chatbots. Gain more understanding of users with sentiment analysis.
Artificial intelligence is not limited to the models described here – and it’s not about what model seems to be the right fit, but what proves to be the right fit. Whatever your right AI model is, we’ll find it!
What does your project need? A scoping session is a great starting point for the AI development process – it help you list all the requirements and jobs to be done. Thanks to that, we can build a team tailored to your needs: including data scientists, software development engineers, designers, or a Scrum Master, estimate the time to deliver, and manage the work efficiently.
With the team selected and educated on your project requirements, it’s time to start the work! During a kickoff meeting, you’ll get to know the team a little better and discuss all the essential points of your collaboration in detail.
Data science projects are managed slightly differently since the models have to learn, but our teams are always loyal to the Scrum methodology. Don’t forget about your role in the development! It’s important for you to participate in the process – go to “Your AI development team” to see why.
The AI model has been trained and tested, your team is learning how to use it right, so it’s time to go live. Depending on the path you’ve taken (stand-alone AI-powered solution or model integration into an existing system), the steps towards launch can be different. And once it’s live, all that’s left is to use AI to the fullest!
AI development involves the work of the data science team, software development engineers, and scrum masters, but it also includes you at the heart of the project – it is all done in collaboration with you and your team to meet all expectations. Artificial Intelligence is not just the algorithms – it’s how it works within your organization, including getting onboard with data-driven culture.
Your domain expert (e.g. head of marketing) or an engineer. Or both. The people who will later work with the model in their daily tasks should participate in the process, too.
Watching over the process, questioning assumptions, suggesting ever better solutions to problems. A person who will consult you if needed.
Data science projects aren’t limited to data work. Software engineers will build your dashboards, interfaces, or a whole new AI-ready program to allow for easy use of the model.
A person who makes sure the team’s work goes as smoothly as possible and facilitates communication between the AI development team and your team.
An absolute must in any data science project. The person who’ll take your data and bring it back to changed like it’s had a makeover.
Need a pretty dashboard? Want to build a full app? The designer will help you turn your ideas into reality that is pretty, usable, and intuitive.
The decision-making person responsible for the success of the project – and involved in the process to accept increments, ask and/or answer questions, specify needs.
The PO proxy is a person who will support you in defining requirements, communicating your needs clearly, and maximizing value derived from the product.
Developing your AI solution can be difficult from the very beginning, and that’s exactly why you might need help kicking off. You might need advisory on the use case, technical know-how to understand what’s achievable, or development power to get the project running.
At Neoteric, we address these needs, building teams adjusted to your requirements, listening to your needs, and making sure communication is always honest and clear. This way, a strong partnership is built: our team works alongside yours to develop an AI-powered solution living up to every expectation.