Artificial intelligence is not all about the sci-fi thing you see in the Hollywood movies which includes super intelligent machines and AI powered robots. The technology has now become mainstream and now used up by businesses which you know or interact on regular basis. For example, Netflix uses AI to make content recommendations while Facebook uses it for image recognition. So based on this examples, it may not come as a surprise for you if you know AI can be used for range of activities like business development and strategic partnerships.
Some of the AI solutions that are built for businesses are virtual sales assistants, predictive analytics and natural language processing.
So you must have by this time heard about chatbots that are AI-powered. There may have popped up situations where you are visiting a website and you will see a chat box appearing suddenly on the screen. Chances are high that it is a bot. In the beginning, chatbots were used just for the purpose of handling customer service but now it has advanced and now turned into AI-powered virtual sales assistants. Now this can mean something as better productivity for your organization.
Just think about the situation where you can follow every lead that comes up time to time. You can make use of some of your virtual sales assistants to come up with some scripts for “follow-up” which you can then use to reach people through email. You can have some of your virtual assistants to focus on meeting scheduling, forecasting or pipeline management. All the efforts are focused on to increase productivity and the apps are working towards reaching it in the faster manner. The use of productivity apps is increasing across organizations to boost the performance of the sales team.
Some companies can perform well using such productivity tools but for others it does not make much sense from strategic point of view. So it is important to ask whether you have some strategy in place so that your customers will have a good experience with bots and will not get frustrated when talking with it. It is important as otherwise the brand value will get affected. Such kind of bot solution will be more useful for businesses which have large volumes of inquiries and not of much use to those organizations which offers customized solutions.
Like any other technology, chatbots has their set of drawbacks too. Chatbots have limited responses and if they are not good enough customers will get frustrated. Again, building chatbots is costly affair and so all kinds of businesses cannot go for it.
If you have large amounts of data about your prospects and partners, then AI can help you put it to use. Moreover, with the use of AI it become helpful for your business to know which leads are more inclined towards turning into final deals as well as which partnerships will help to make profits for your business.
This kind of thoughts is what makes AI-powered tools better and good to be used. With predictive analytics you will be able to work on the number and analyse it so as to know which leads can be beneficial for your business. For example, just as Facebook makes use of AI to know what you like on your news feed and would like to engage, in the similar manner companies can make use of AI solutions to know what kind of content potential partners will resonate with.
Predictive analytics can come in handy when you have large volumes of data. However, you will need to come up with models which can work over time and learn to use them and this can take some longer time. When working with predictive analytics the results can be decided based on the quality of the algorithms. If an organization wants to involve in decision making process that is data-driven then it will have to gain access to a good amount of relevant data from different activities and at times gaining access to such large volumes of data is not easy to come by.
How well such techniques will work can be judged by critical factors like time. It is true that a said predictive model can work for an organization for a specific amount of time but with time as customer behaviour changes it will also have to be updated in order to stay with the trend. If a business plans to get into predictive analytics it will need bulk amount of data which can then be exploited to use its power. Again, results in terms of recommendations and predictions get better with time and so all you have to do is to wait patiently.
Generally predictive analytics is beneficial for businesses still there are exceptions, especially when the company cannot manage to have large volumes of data. Again, there are businesses which offer completely customized solutions to the customers in terms of proposals, pricing and solutions. So only human interventions can be possible and AI cannot completely work on its own for evaluation. Exception management is a common roadblock which you have to face with predictive analytics and lack of historical data leading to insufficient decisions is another issue.
Organizations which has large volumes of data available with them can use them in optimized manner for improving business aspects like project timelines, project delivery and cost by completely exploiting the power of predictive analytics.
The ability of machines to understand the speech of humans is termed as Natural Language Processing and you can use AI for the same. Based on this technology Alexa or Siri can understand the voice commands you send. In the similar way you can make use of AI to look for conversations over the social media and get an idea about what people are thinking and talking about. You can also recognize emotional sentiment by training AI.
Suppose you are planning to come up with an innovative idea to be used in your strategic partnerships. For the same you need to know what customers want. So you plan to make use of AI powered tools in order to track and monitor social media conversations of the users everywhere on the internet and based on your finding come up with new product ideas, find new trends or know about unmet needs of consumers.
We all know that NLP is effective but before you plan to implement it, you should ask a few questions and thereby try to know what issues you are addressing with it and how you plan to resolve them. Keep in mind that you need large volumes of data of users to make it work effectively.
When we talk about NLP we cannot point out much of its disadvantages but you can say that it comes with some limitations. NLP is not a completely matured technology but very ambitious in nature. Again you need to have good amount of time to be spend on linguistic edge case-testing before you can actually use the model completely and this can be a hindrance to the organization which does not have enough resource or time to spend on the process to complete. This means that you will need to have substantial amount of time to work on the models and train them so as to ensure NLP works. In the beginning you will have to face challenges related to homographs as the model will end up giving you inaccurate results because it will get confused between two words with same spelling but with different meanings.
Overall, if we look at the technology solution that comes from artificial intelligence you can say that they have positive effect on the organizations. They can help to make the development team more productive, efficient and profitable.