The fast pace of artificial intelligence (AI) and automation is propelling strategists to reshape their business models. This is fostering the integration of AI in the business processes but the consequences of this adoption are underexplored and needs attention. This paper focuses on the overall impact of AI on businesses -from research, innovation, market deployment to future shifts in business models. To access this overall impact, we design a three dimensional research model, based upon the Neo-Schumpeterian economics and its three forces viz. innovation, knowledge, and entrepreneurship. The first dimension deals with research and innovation in AI. In the second dimension, we explore the influence of AI on the global market and the strategic objectives of the businesses and finally the third dimension examines how AI is shaping business contexts. Additionally, the paper explores AI implications on actors and its dark sides.

A label-free technique for the detection of triacylglycerides by a localized surface plasmon resonance (LSPR)-based biosensor is demonstrated. An LSPR-based fiber-optic sensor probe is fabricated by immobilizing lipase enzyme on silver nanoparticles (Ag-NPs) coated on an unclad segment of a plastic clad optical fiber. The size and shape of nanoparticles were characterized by high-resolution transmission electron microscopy and UV-visible spectroscopy. The peak absorbance wavelength changes with concentration of triacylglycerides surrounding the sensor probe, and sensitivity is estimated from shift in the peak absorbance wavelength as a function of concentration. The fabricated sensor was characterized for the concentration of triacylglyceride solution in the range 0 to 7 mM. The sensor shows the best sensitivity at a temperature of 37°C and pH 7.4 of the triacylglycerides emulsion with a response time of 40 s. A sensitivity of 28.5  nm/mM of triacylglyceride solution is obtained with a limit of detection of 0.016 mM in the entire range of triacylglycerides. This compact biosensor shows good selectivity, stability, and reproducibility in the entire physiological range of triacylglycerides and is well-suited to real-time online monitoring and remote sensing.

We here propose a simple numerical procedure to calculate the cutoff frequencies in optical fibers with any arbitrary refractive index profile including discrete numerical data from profile measurement. The cutoff problem is transformed into a matrix eigenvalue problem and the cutoff frequencies can be obtained by determining the eigenvalues of a matrix with elements given by simple expressions.

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