Future Trends in Data Management: What Businesses Need to Know
Looking ahead, expect to see generative AI trends focused on three main pools: quick and sweeping technological advances, faster-than-expected digital transformations, and increasing emphasis on the societal and global impact of artificial intelligence.
Future Trends for Data Management
These specific predictions and growing trends are most likely on the horizon:
1. Multimodality will Rise
Data management is increasingly focusing on multimodality, which is the ability of a machine or software to accept inputs and produce outputs in multiple formats. In this data-driven world, artificial intelligence and machine learning models are progressively embracing data in a variety like text, images, audios, or videos.
But a majority of AI-producing companies like Microsoft are still unable to evolve full-fledged multimodal capacities. The future trend may be named after them because more versatile AI is the need of the hour. You can expect an advanced version of apps like Chat GPT to refine and evolve into an advanced version of OpenAI. It can help in commanding the tool to process, enrich, or sanitize a database in a customized format. Very soon, its text-to-video tool called Sora-like Tools will be all over the internet, overcoming the limitations of data management.
2. Embrace AI as a Service
The future is going to be an AI-as-a-service-driven world. The popularity of generative AI is obvious. But its aggressive version is yet to come. It is expensive to bear the cost of developing your own AI infrastructure and teams. Hiring consultants and managed service providers will make it more feasible to evolve AI models for automatically handling data management challenges.
This trend will make the growth of AI models more aggressive as a service. This is how offering customizable, lightweight, or open-source models can be easily built to attract a broad range of customers. Additionally, services that focus on AI governance and security will be in high demand.
3. Shifting to AGI and Related Research
AGI, or Artificial General Intelligence, is well known as a type of artificial intelligence with advanced capability to outperform in many tasks, especially when it requires critical thinking.
However, it is only a dream to introduce this capacity in a machine. But leading companies like Google’s DeepMind, OpenAI, Meta, Adept AI, and others are putting in a lot of effort to find ways.
As far as the current environment is concerned, companies are standing alone to achieve it. But collaboration can be a way to achieve success in it. Though it’s far off, AGI is gradually achieving its goal. AI companies will continuously evolve generative AI for managing data and other tasks.
4. Workforce Reformation
Generative AI is likely to transform the workforce, but experts are divided on whether it will be good or bad for employees. Some of them believe that it will help employees automate routine tasks. It means that this evolving technology can transform practices in data collection, recommendations, and data analytics. On the flip side, some are skeptical.
Certainly, this evolving technology can make tasks like emailing, reporting, managing data, and generating content way easier. This means that the strategists would have more time to emphasize higher-level strategic tasks.
Whatever the future of AGI is, it is likely to impact a broad range of jobs across different industries. Even today, you can see how tools like Tableau and Octaparse are already sparking concerns about job loss. However, the future workforce may see effects, for sure.
In order to address these uncertainties, businesses and educational institutions have started bringing training for developing generative AI apps into the mainstream.
5. Regulatory Pressures Will Be More
Considering the significance of the misuse of AI, the EU AI Act was introduced in March 2024. This regulation was drafted to monitor the use of AI and also protect EU citizen data. This will certainly impact all organizations that use this technology within the dimension of the EU or its data. This is the first regulation of its kind, and it is likely to be a milestone for future regulations regarding AI. Europe is following in the footsteps of US states like California, Virginia, and Colorado, which have their own AI regulations and guidelines for using generative AI.
So, there will be a trend to regulate data-based activities to mitigate the risk of cybercrime.
6. Stress on Security, Privacy, and Governance
With the widespread use of data-driven scams like CA Analytica, it is necessary to regulate data with strong data management policies. The overwhelming use and research of AI by companies and businesses will require more investment in its governance and security. Strong policies are required to address vulnerabilities.
Considering the risk, many companies have pulled up their sleeves to strengthen their AI governance. This trend will become more popular as the associated risks of vulnerability increase. The future trend can be to deploy dedicated AI governance and security platforms with human-in-the-loop monitoring. A missing link will attract reputational damages and increase liabilities.
7. Greater Focus on Quality
In the coming years, the pressure will be on data management companies. The government, regulatory bodies, businesses, and users are more alert. They focus on flawed, stolen, or malicious data produced by generative AI to control it proactively. Many data-based companies have started taking measures in response and have adopted transparency to win the trust of data subjects.
Google’s Gemini is its appropriate example, which allows users to rate responses, suggest changes, report, and verify content or legal issues.
8. Widespread Use of AI Tools
Many companies are employing generative AI to improve the customer experience. They are integrating it into customer-facing tools so that the internal workflows and user experience can be excellent. Chat GPT 4 is its biggest example. You can expect a more aggressive version of these applications, especially for data management services. This practice will reduce the use of tools that fail to tailor data management solutions and recommendations for research, shopping, or anything else.
Conclusion
Data management trends will be more inclined toward generative AI in the future. The technology will be enhanced to a great extent, tailoring data management needs and research services.
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