Artificial intelligence (AI) and machine learning - these terms cease to be the theory of the future, but gain real application. The Forbes Insights poll, together with Dell Technologies and Intel, showed that AI is a key component of digital development, but only a quarter of the CxO (Chief experience officer) surveyed say they have implemented these technologies in their company. What is the reason for such low AI penetration in organizations and is your company ready to use machine learning? In this article, we will share our thoughts on the impact of AI on a business and how to implement it faster.
Is Your Business Ready for Artificial Intelligence (AI)?
Over the past 50 years, business has been actively automating processes. In the near future, we will completely get rid of manual processing of information - it will be replaced by autonomous systems capable of processing huge amounts of information with high speed. If the business accepts digital realities and introduces new technologies into its work, it will be able to improve productivity and financial efficiency significantly. It’s not enough just to produce a product or service now - it is important to establish communication with the consumer. Only a client can evaluate the provided service and make a conclusion about his work. Therefore, product improvement according to user experience becomes the key to effective business. This applies to both B2B and B2C companies.
Automation, flexibility, simplicity are terms that must be clearly integrated into any organization processes. Thanks to the efficient use of resources, your company will increase customer loyalty and will have a competitive advantage over other market players. What is necessary in order to start using machine learning tomorrow and get benefits?
- Create or adjust your role in the automation process and instill a new corporate culture.
- Assemble an ideological team of specialists who are ready to face the difficulties of mastering new technologies.
- Prepare data for artificial intelligence training.
- Choose a machine learning platform or service provider that provides AI as a service or develop your own solution.
- Train your own specialists, because it will be very expensive to search for ones in the market.
- Run, test and implement the project.
From theory to practice
Now let's talk about the companies that effectively use new technologies in their strategies.
- Google - Neural Networks
The company's most significant achievement is the creation of machines in DeepMind that can dream and create unusual images.
Google is committed to exploring all aspects of machine learning, which helps the company improve classical algorithms, as well as process natural speech more efficiently and translate it, improve ranking and predictive systems.
- Pinterest - Content Search
The main function of the Pinterest social network is content curation. And the company is doing everything possible to increase the efficiency of this process, including the use of machine learning.
Today, machine learning is involved in every aspect of Pinterest’s business operations, from moderation of spam and content searches to monetizing ads and reducing the number of unsubscribes from newsletters.
- IBM - Next Generation Healthcare
The largest technology corporation IBM is abandoning an outdated business model and is actively exploring new directions. The brand’s most famous product today is Watson Artificial Intelligence.
Over the past few years, Watson has been used in hospitals and medical centers where it has diagnosed certain types of cancer more effectively than oncologists.
Watson also has huge retail potential where it can serve as a consultant. IBM offers its license-based product, making it unique and affordable.
The AI future.
Very soon, artificial intelligence will be able to learn much more efficiently: machines will improve with minimal human involvement.2. Automation of the fight against cyber attacks
The rise of cybercrime is forcing companies to think about defenses. Soon, AI will play an increasingly important role in monitoring, preventing and responding to cyber attacks.3. Convincing generative models
Soon we will not be able to distinguish machines from people at all. In the future, algorithms will be able to create pictures, imitate human speech and even entire personalities.4. Quick training
Even the most complex artificial intelligence needs a huge amount of data for training. Soon, machine learning systems will require less and less information and time.
Black and White in Machine Learning
But, unfortunately, the technologies are imperfect, and human skepticism for their implementation is still high. A fresh IDC report claims that AI and machine learning will increase productivity by 4 times in the foreseeable future, and 2.5 million industrial robots will work in industries around the world. In 2020, about 30% of all office work will be automated, and by 2021, 20% of corporate applications will be working using AI.
It sounds great, but in practice most companies still use manual labor to process the data. Their corporate culture, inertia and unwillingness to apply new technologies hinder business development.