The technology sector is showing its strength. Like every sector reacts to transition and transformation, technology providers are more than ever depended upon to support remote working, food and resources access, health care, networking, accessibility and entertainment.
Innovation remains a must. While it is difficult to anticipate the near-term market and economic landscape, it is clear that consumers and businesses will need new methods , ideas and approaches.
However, it can be risky and expensive — to break barriers. In the face of severe market volatility and worldwide pressure, tech firms need to flex their agility and continue their development strategy with a clear vision.
Can tech leaders remain competitive with the increased rate of change while efficiently traversing the changing threat landscape? Technology leaders will need to recognise the equilibrium between innovation and risk holistically and intentionally, to scale effectively over the long term.
Here are a few hotbeds of innovative opportunities and some of the risks that these endeavors may face.
With more business going digital, the volume of data being collected is steadily increasing. From companies’ on-site systems to personal telecommunications and IoT devices and remote business-enablement software, the use of digital tools — and data from those tools — is growing every day. Advanced analytics may be used by companies that exploit the power of such information by effectively managing their data to draw meaningful insights and be better positioned to compete.
From a product and service point of view, information management solutions are the critical halfway point to effective storage, ethics, compliance and analysis. Data management and confidentiality-as-a-service can help companies maintain loyalty among users and government agencies, while obtaining value from their data.
The new California Consumer Privacy Act (CCPA) and the European General Data Protection Regulation (GDPR) give individuals possession of their information, adding to the data management and governance obligations of tech companies.
The proposed tracking and tracing methods to fight coronavirus spread may be a new era in privacy concerns. In any situation, meeting and surpassing the requirements of the various states and countries regulating data privacy will be essential for tech firms to restore and maintain consumer confidence. After all, the fall in consumer confidence in your products for most software companies compared to those of your competitors can significantly impact revenue and market share in both the short and long term.
Artificial Intelligence (AI)
Outside of regulatory and trust considerations, prior to the epidemic, 29 per cent of the tech CFOs surveyed said that data leak was a major threat to their business. Trying to attract important data generated and stored by tech companies, cyber hacks will continue to affect the industry with growing complexity, potentially leading to greater losses and erosion of trust — unless companies effectively mitigate this.
Concurrently, AI is making a distinction of industry, expanding the opportunities for technological innovation and joint ventures. In healthcare, for example, AI-based solutions turn medical instruments into health monitoring devices and enable smartphones to operate as clinical diagnostics and X-ray image readers.
AI is also progressively being used to increase recruitment processes to address labor concerns. From chatbots to interview schedules and talent-matching, tech companies can look to AI for talent management support.
There are unprecedented hurdles stemming from AI, face recognition and other emerging technology.
As a result of poor data or implicit bias on the part of software developers, operator error may become intense once it has been introduced into AI. These risks are heightened by the fact that tech firms are faced with backlash due to lack of diversity in their ranks, in addition to biased strategies. Algorithmic bias can cause severe damage to business operations and reputation.
There is also an overarching dilemma regarding the possibility of robots filling human-staffed jobs. AI, unlike robotic process automation (RPA), is designed not to be rules-based, but to refine the algorithm as it gathers more and more data, effectively training itself and becoming smarter over time.
Around the same moment, accountability issues resound. From weaponising AI to hacking devices, manipulating political campaigns through deep-featured videos, or unwittingly exposing secret data by sorting and linking procedures, business leaders would need to show their good ethics and understand that they should be responsible for all future applications of their technologies.
Robotic Process Automation (RPA)
Many CFOs say that juggling a growing amount of work and higher demands is one of their biggest personal challenges. RPA, a software-based approach, provides solutions for routine and manual operations. RPA can take over duties, including filing system, form enforcement, database entries, site scrapping, analyses and stats, among other rules-based programs.
By utilising RPA, tech firms can move the attention of staff to more strategic jobs, further enhancing the company's potential to evolve. RPA will also increase the efficiency of the workforce and attract talent by removing time-consuming, repetitive tasks that practitioners find burdensome or ineffective.
When growing work volumes and ballooning standards contribute to the introduction of RPA solutions, data protection and privacy threats can unintentionally be added. Improper usage of data and automatic access may contribute to unintended errors and liabilities, suggesting that enhanced security safeguards will be needed for RPA device adoption.
Develop the fifth generation of mobile cellular networking networks and network — known as 5G — is the starting point for improving data transmission rates and smartphone compatibility. This allows quicker updates and more mobile company processes with improved access to data-dense apps.
5 G pave the foundations for wider broadband infrastructure that could fuel, potential driverless vehicles, boost public infrastructure, deliver critical healthcare services, and more, build possibilities for services intersecting sectors.
Continued geopolitical instability, strengthening of boundaries, rigid protection of intellectual property and limits on trade are key concerns for the technology sector, particularly when they relate to national security and innovation.
As China marches on of the first 5G mobile networks, American tech supremacy is coming under siege. The U.S. must catch up quickly without compromising the security of its networks.
5G technology, which is expected to "serve as a backbone for trillions of dollars’ worth of economic and technological activity," faces constraints in the U.S. due to security issues surrounding known bugs that could serve as possible entry points for hackers.
Digital Ledger Technology (DLT) offers greater transparency of data, improved security and quicker transaction times, which could appeal to many tech companies and their customers, especially with less face-to - face transactions.
Fintech and banking start-ups use blockchain to build cryptocurrencies and crypto software, thus removing the need for centralized financial intermediaries and supplying consumers with access to decentralised digital assets.
Around the same time, the entertainment industry is tackling artistic ownership by recording intellectual property rights through chain-of-title documents as well as smart contracts. Smart contracts — a way of streamlining and monitoring payment records — also help digital marketers who can use technologies to fight fraud.
The untapped potential of Blockchain and DLT also illuminates the dark side of this technology: scalability, legal grey ground due to lack of regulations, electricity usage prices, dubious network durability and security and data protection concerns.
"Blockchain privacy poisoning" can pose a potentially important threat to the credibility of this technology. Privacy poisoning refers to the inclusion of sensitive data — an instance of an individual's name along with some of the 29 additional private items — in the series. Because a blockchain produces a collection of permanent databases, it can be extremely difficult to comply with data protection regulations.
There is a great deal of potential to access blockchain technologies, but there are several variables yet to be identified.
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